GIST-small-topic

A fine-tuned version of the bert architecture (BertForSequenceClassification) optimized for the text-classification task.

• Model type: bert
• Problem Type: single_label_classification
• Number of Labels: 27
• Vocabulary Size: 30522
• License: MIT

Use

To get started with this model in Python using the Hugging Face Transformers library, run the following code:

from transformers import AutoTokenizer, AutoModelForSequenceClassification
import torch

model_id = "agentlans/GIST-small-topic"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForSequenceClassification.from_pretrained(model_id)

text = "Replace this with your input text."
inputs = tokenizer(text, return_tensors="pt")

with torch.no_grad():
    logits = model(**inputs).logits

predicted_class_id = logits.argmax().item()
predicted_class_name = model.config.id2label[predicted_class_id]

print(f"Predicted Class ID: {predicted_class_id}")
print(f"Predicted Class Name: {predicted_class_name}")

Intended Uses & Limitations

Intended Use

This model is designed for sequence classification tasks. Below are the specific class labels mapped to their corresponding IDs:

Label ID	Label Name
0	Art & Design
1	Arts & Entertainment
2	Autos & Vehicles
3	Beauty & Fitness
4	Books & Literature
5	Business & Industry
6	Education & Careers
7	Electronics & Hardware
8	Finance & Investment
9	Food & Drink
10	Games & Recreation
11	Health & Wellness
12	Hobbies & Leisure
13	Home & Gardening
14	Industrial & Manufacturing
15	Internet & Telecom
16	Law & Government
17	News & Politics
18	People & Society
19	Real Estate & Property
20	Religion & Society
21	Science & Research
22	Shopping & Retail
23	Software Applications
24	Software Engineering
25	Sports & Athletics
26	Travel & Transportation

Training Details

Hyperparameters

The following hyperparameters were used during fine-tuning:

• Learning Rate: 5e-05
• Train Batch Size: 8
• Eval Batch Size: 8
• Optimizer: OptimizerNames.ADAMW_TORCH_FUSED
• Number of Epochs: 3.0
• Mixed Precision: BF16

Show Advanced Training Configuration

Optimization & Regularization

• Gradient Accumulation Steps: 1
• Learning Rate Scheduler: SchedulerType.LINEAR
• Warmup Steps: 0
• Warmup Ratio: None
• Weight Decay: 0.0
• Max Gradient Norm: 1.0

Hardware & Reproducibility

• Number of GPUs: 1
• Seed: 42

Training Results & Evaluation

During fine-tuning, the model achieved the following results on the evaluation set:

Metric	Value
Train Loss	0.2626
Validation Loss	0.339
Validation F1 Score	0.918
Total FLOPs	2.7880e+16

For performance on the test set, click here.

Speed Performance

• Training Runtime: 3658.4093 seconds
• Train Samples per Second: 462.558
• Evaluation Runtime: 34.4313 seconds
• Eval Samples per Second: 1820.318

Show Detailed Training Logs

Training Logs History

Step	Epoch	Learning Rate	Training Loss	Validation Loss	Validation F1
500	0.007	4.9882e-05	2.2193	N/A	N/A
1000	0.014	4.9764e-05	1.0628	N/A	N/A
1500	0.021	4.9646e-05	0.7231	N/A	N/A
2000	0.028	4.9527e-05	0.562	N/A	N/A
2500	0.035	4.9409e-05	0.5424	N/A	N/A
3000	0.043	4.9291e-05	0.4953	N/A	N/A
3500	0.05	4.9173e-05	0.4707	N/A	N/A
4000	0.057	4.9055e-05	0.463	N/A	N/A
4500	0.064	4.8937e-05	0.4627	N/A	N/A
5000	0.071	4.8818e-05	0.4857	N/A	N/A
5500	0.078	4.8700e-05	0.4378	N/A	N/A
6000	0.085	4.8582e-05	0.4585	N/A	N/A
6500	0.092	4.8464e-05	0.4272	N/A	N/A
7000	0.099	4.8346e-05	0.4389	N/A	N/A
7500	0.106	4.8227e-05	0.4305	N/A	N/A
8000	0.113	4.8109e-05	0.411	N/A	N/A
8500	0.121	4.7991e-05	0.4347	N/A	N/A
9000	0.128	4.7873e-05	0.4178	N/A	N/A
9500	0.135	4.7755e-05	0.3853	N/A	N/A
10000	0.142	4.7637e-05	0.412	N/A	N/A
10500	0.149	4.7518e-05	0.4097	N/A	N/A
11000	0.156	4.7400e-05	0.3976	N/A	N/A
11500	0.163	4.7282e-05	0.4267	N/A	N/A
12000	0.17	4.7164e-05	0.4051	N/A	N/A
12500	0.177	4.7046e-05	0.4136	N/A	N/A
13000	0.184	4.6927e-05	0.4314	N/A	N/A
13500	0.191	4.6809e-05	0.4078	N/A	N/A
14000	0.199	4.6691e-05	0.4009	N/A	N/A
14500	0.206	4.6573e-05	0.3848	N/A	N/A
15000	0.213	4.6455e-05	0.4049	N/A	N/A
15500	0.22	4.6336e-05	0.41	N/A	N/A
16000	0.227	4.6218e-05	0.4126	N/A	N/A
16500	0.234	4.6100e-05	0.3992	N/A	N/A
17000	0.241	4.5982e-05	0.3684	N/A	N/A
17500	0.248	4.5864e-05	0.3818	N/A	N/A
18000	0.255	4.5746e-05	0.3849	N/A	N/A
18500	0.262	4.5627e-05	0.3842	N/A	N/A
19000	0.269	4.5509e-05	0.3888	N/A	N/A
19500	0.277	4.5391e-05	0.3992	N/A	N/A
20000	0.284	4.5273e-05	0.3959	N/A	N/A
20500	0.291	4.5155e-05	0.3969	N/A	N/A
21000	0.298	4.5036e-05	0.4233	N/A	N/A
21500	0.305	4.4918e-05	0.3926	N/A	N/A
22000	0.312	4.4800e-05	0.3883	N/A	N/A
22500	0.319	4.4682e-05	0.3796	N/A	N/A
23000	0.326	4.4564e-05	0.3921	N/A	N/A
23500	0.333	4.4445e-05	0.3867	N/A	N/A
24000	0.34	4.4327e-05	0.382	N/A	N/A
24500	0.347	4.4209e-05	0.3494	N/A	N/A
25000	0.355	4.4091e-05	0.4018	N/A	N/A
25500	0.362	4.3973e-05	0.3708	N/A	N/A
26000	0.369	4.3855e-05	0.3966	N/A	N/A
26500	0.376	4.3736e-05	0.4013	N/A	N/A
27000	0.383	4.3618e-05	0.3455	N/A	N/A
27500	0.39	4.3500e-05	0.3923	N/A	N/A
28000	0.397	4.3382e-05	0.3778	N/A	N/A
28500	0.404	4.3264e-05	0.3652	N/A	N/A
29000	0.411	4.3145e-05	0.3851	N/A	N/A
29500	0.418	4.3027e-05	0.3951	N/A	N/A
30000	0.425	4.2909e-05	0.3763	N/A	N/A
30500	0.433	4.2791e-05	0.3698	N/A	N/A
31000	0.44	4.2673e-05	0.3606	N/A	N/A
31500	0.447	4.2554e-05	0.3391	N/A	N/A
32000	0.454	4.2436e-05	0.3729	N/A	N/A
32500	0.461	4.2318e-05	0.3907	N/A	N/A
33000	0.468	4.2200e-05	0.3769	N/A	N/A
33500	0.475	4.2082e-05	0.3468	N/A	N/A
34000	0.482	4.1964e-05	0.3394	N/A	N/A
34500	0.489	4.1845e-05	0.3842	N/A	N/A
35000	0.496	4.1727e-05	0.3564	N/A	N/A
35500	0.503	4.1609e-05	0.3977	N/A	N/A
36000	0.511	4.1491e-05	0.3546	N/A	N/A
36500	0.518	4.1373e-05	0.3628	N/A	N/A
37000	0.525	4.1254e-05	0.3952	N/A	N/A
37500	0.532	4.1136e-05	0.3673	N/A	N/A
38000	0.539	4.1018e-05	0.3646	N/A	N/A
38500	0.546	4.0900e-05	0.3723	N/A	N/A
39000	0.553	4.0782e-05	0.3248	N/A	N/A
39500	0.56	4.0663e-05	0.352	N/A	N/A
40000	0.567	4.0545e-05	0.3465	N/A	N/A
40500	0.574	4.0427e-05	0.3654	N/A	N/A
41000	0.581	4.0309e-05	0.3689	N/A	N/A
41500	0.589	4.0191e-05	0.3718	N/A	N/A
42000	0.596	4.0073e-05	0.3648	N/A	N/A
42500	0.603	3.9954e-05	0.331	N/A	N/A
43000	0.61	3.9836e-05	0.3337	N/A	N/A
43500	0.617	3.9718e-05	0.3748	N/A	N/A
44000	0.624	3.9600e-05	0.3221	N/A	N/A
44500	0.631	3.9482e-05	0.3596	N/A	N/A
45000	0.638	3.9363e-05	0.3437	N/A	N/A
45500	0.645	3.9245e-05	0.3619	N/A	N/A
46000	0.652	3.9127e-05	0.3573	N/A	N/A
46500	0.659	3.9009e-05	0.3212	N/A	N/A
47000	0.667	3.8891e-05	0.3341	N/A	N/A
47500	0.674	3.8773e-05	0.3368	N/A	N/A
48000	0.681	3.8654e-05	0.3473	N/A	N/A
48500	0.688	3.8536e-05	0.3434	N/A	N/A
49000	0.695	3.8418e-05	0.3339	N/A	N/A
49500	0.702	3.8300e-05	0.3438	N/A	N/A
50000	0.709	3.8182e-05	0.3536	N/A	N/A
50500	0.716	3.8063e-05	0.3545	N/A	N/A
51000	0.723	3.7945e-05	0.3538	N/A	N/A
51500	0.73	3.7827e-05	0.3631	N/A	N/A
52000	0.737	3.7709e-05	0.349	N/A	N/A
52500	0.745	3.7591e-05	0.3175	N/A	N/A
53000	0.752	3.7472e-05	0.374	N/A	N/A
53500	0.759	3.7354e-05	0.3238	N/A	N/A
54000	0.766	3.7236e-05	0.3377	N/A	N/A
54500	0.773	3.7118e-05	0.3612	N/A	N/A
55000	0.78	3.7000e-05	0.3217	N/A	N/A
55500	0.787	3.6882e-05	0.3337	N/A	N/A
56000	0.794	3.6763e-05	0.3527	N/A	N/A
56500	0.801	3.6645e-05	0.3708	N/A	N/A
57000	0.808	3.6527e-05	0.3303	N/A	N/A
57500	0.815	3.6409e-05	0.3445	N/A	N/A
58000	0.823	3.6291e-05	0.3377	N/A	N/A
58500	0.83	3.6172e-05	0.339	N/A	N/A
59000	0.837	3.6054e-05	0.3516	N/A	N/A
59500	0.844	3.5936e-05	0.3146	N/A	N/A
60000	0.851	3.5818e-05	0.3382	N/A	N/A
60500	0.858	3.5700e-05	0.3618	N/A	N/A
61000	0.865	3.5581e-05	0.2988	N/A	N/A
61500	0.872	3.5463e-05	0.3718	N/A	N/A
62000	0.879	3.5345e-05	0.3372	N/A	N/A
62500	0.886	3.5227e-05	0.3544	N/A	N/A
63000	0.893	3.5109e-05	0.3471	N/A	N/A
63500	0.901	3.4991e-05	0.3058	N/A	N/A
64000	0.908	3.4872e-05	0.3226	N/A	N/A
64500	0.915	3.4754e-05	0.3254	N/A	N/A
65000	0.922	3.4636e-05	0.3266	N/A	N/A
65500	0.929	3.4518e-05	0.3359	N/A	N/A
66000	0.936	3.4400e-05	0.3403	N/A	N/A
66500	0.943	3.4281e-05	0.332	N/A	N/A
67000	0.95	3.4163e-05	0.3309	N/A	N/A
67500	0.957	3.4045e-05	0.3341	N/A	N/A
68000	0.964	3.3927e-05	0.328	N/A	N/A
68500	0.971	3.3809e-05	0.3043	N/A	N/A
69000	0.979	3.3690e-05	0.3407	N/A	N/A
69500	0.986	3.3572e-05	0.3462	N/A	N/A
70000	0.993	3.3454e-05	0.325	N/A	N/A
70500	1.0	3.3336e-05	0.3255	N/A	N/A
70510	1.0	N/A	N/A	0.313	0.9001
71000	1.007	3.3218e-05	0.234	N/A	N/A
71500	1.014	3.3100e-05	0.2453	N/A	N/A
72000	1.021	3.2981e-05	0.233	N/A	N/A
72500	1.028	3.2863e-05	0.2428	N/A	N/A
73000	1.035	3.2745e-05	0.2641	N/A	N/A
73500	1.042	3.2627e-05	0.2644	N/A	N/A
74000	1.049	3.2509e-05	0.2474	N/A	N/A
74500	1.057	3.2390e-05	0.2456	N/A	N/A
75000	1.064	3.2272e-05	0.2471	N/A	N/A
75500	1.071	3.2154e-05	0.2594	N/A	N/A
76000	1.078	3.2036e-05	0.2571	N/A	N/A
76500	1.085	3.1918e-05	0.2608	N/A	N/A
77000	1.092	3.1800e-05	0.2453	N/A	N/A
77500	1.099	3.1681e-05	0.2633	N/A	N/A
78000	1.106	3.1563e-05	0.2341	N/A	N/A
78500	1.113	3.1445e-05	0.2639	N/A	N/A
79000	1.12	3.1327e-05	0.2641	N/A	N/A
79500	1.127	3.1209e-05	0.2338	N/A	N/A
80000	1.135	3.1090e-05	0.2726	N/A	N/A
80500	1.142	3.0972e-05	0.2452	N/A	N/A
81000	1.149	3.0854e-05	0.2721	N/A	N/A
81500	1.156	3.0736e-05	0.2468	N/A	N/A
82000	1.163	3.0618e-05	0.2326	N/A	N/A
82500	1.17	3.0499e-05	0.2659	N/A	N/A
83000	1.177	3.0381e-05	0.286	N/A	N/A
83500	1.184	3.0263e-05	0.253	N/A	N/A
84000	1.191	3.0145e-05	0.2709	N/A	N/A
84500	1.198	3.0027e-05	0.2607	N/A	N/A
85000	1.206	2.9909e-05	0.2577	N/A	N/A
85500	1.213	2.9790e-05	0.2547	N/A	N/A
86000	1.22	2.9672e-05	0.2473	N/A	N/A
86500	1.227	2.9554e-05	0.2585	N/A	N/A
87000	1.234	2.9436e-05	0.2406	N/A	N/A
87500	1.241	2.9318e-05	0.2393	N/A	N/A
88000	1.248	2.9199e-05	0.2565	N/A	N/A
88500	1.255	2.9081e-05	0.2656	N/A	N/A
89000	1.262	2.8963e-05	0.2835	N/A	N/A
89500	1.269	2.8845e-05	0.2288	N/A	N/A
90000	1.276	2.8727e-05	0.2764	N/A	N/A
90500	1.284	2.8608e-05	0.2681	N/A	N/A
91000	1.291	2.8490e-05	0.2662	N/A	N/A
91500	1.298	2.8372e-05	0.2417	N/A	N/A
92000	1.305	2.8254e-05	0.252	N/A	N/A
92500	1.312	2.8136e-05	0.2455	N/A	N/A
93000	1.319	2.8018e-05	0.2357	N/A	N/A
93500	1.326	2.7899e-05	0.2548	N/A	N/A
94000	1.333	2.7781e-05	0.2323	N/A	N/A
94500	1.34	2.7663e-05	0.2401	N/A	N/A
95000	1.347	2.7545e-05	0.2893	N/A	N/A
95500	1.354	2.7427e-05	0.2555	N/A	N/A
96000	1.362	2.7308e-05	0.2379	N/A	N/A
96500	1.369	2.7190e-05	0.2599	N/A	N/A
97000	1.376	2.7072e-05	0.2185	N/A	N/A
97500	1.383	2.6954e-05	0.2662	N/A	N/A
98000	1.39	2.6836e-05	0.2474	N/A	N/A
98500	1.397	2.6717e-05	0.2421	N/A	N/A
99000	1.404	2.6599e-05	0.2469	N/A	N/A
99500	1.411	2.6481e-05	0.2515	N/A	N/A
100000	1.418	2.6363e-05	0.269	N/A	N/A
100500	1.425	2.6245e-05	0.2611	N/A	N/A
101000	1.432	2.6127e-05	0.2498	N/A	N/A
101500	1.44	2.6008e-05	0.2395	N/A	N/A
102000	1.447	2.5890e-05	0.2485	N/A	N/A
102500	1.454	2.5772e-05	0.2651	N/A	N/A
103000	1.461	2.5654e-05	0.2453	N/A	N/A
103500	1.468	2.5536e-05	0.2502	N/A	N/A
104000	1.475	2.5417e-05	0.2695	N/A	N/A
104500	1.482	2.5299e-05	0.2017	N/A	N/A
105000	1.489	2.5181e-05	0.2484	N/A	N/A
105500	1.496	2.5063e-05	0.2515	N/A	N/A
106000	1.503	2.4945e-05	0.241	N/A	N/A
106500	1.51	2.4827e-05	0.2256	N/A	N/A
107000	1.518	2.4708e-05	0.2318	N/A	N/A
107500	1.525	2.4590e-05	0.2301	N/A	N/A
108000	1.532	2.4472e-05	0.2231	N/A	N/A
108500	1.539	2.4354e-05	0.2509	N/A	N/A
109000	1.546	2.4236e-05	0.2586	N/A	N/A
109500	1.553	2.4117e-05	0.2365	N/A	N/A
110000	1.56	2.3999e-05	0.2497	N/A	N/A
110500	1.567	2.3881e-05	0.2157	N/A	N/A
111000	1.574	2.3763e-05	0.2511	N/A	N/A
111500	1.581	2.3645e-05	0.2574	N/A	N/A
112000	1.588	2.3526e-05	0.2552	N/A	N/A
112500	1.596	2.3408e-05	0.2297	N/A	N/A
113000	1.603	2.3290e-05	0.2502	N/A	N/A
113500	1.61	2.3172e-05	0.2236	N/A	N/A
114000	1.617	2.3054e-05	0.2252	N/A	N/A
114500	1.624	2.2936e-05	0.23	N/A	N/A
115000	1.631	2.2817e-05	0.2342	N/A	N/A
115500	1.638	2.2699e-05	0.2287	N/A	N/A
116000	1.645	2.2581e-05	0.2582	N/A	N/A
116500	1.652	2.2463e-05	0.2402	N/A	N/A
117000	1.659	2.2345e-05	0.2409	N/A	N/A
117500	1.666	2.2226e-05	0.2621	N/A	N/A
118000	1.674	2.2108e-05	0.2373	N/A	N/A
118500	1.681	2.1990e-05	0.239	N/A	N/A
119000	1.688	2.1872e-05	0.2454	N/A	N/A
119500	1.695	2.1754e-05	0.244	N/A	N/A
120000	1.702	2.1635e-05	0.2476	N/A	N/A
120500	1.709	2.1517e-05	0.2261	N/A	N/A
121000	1.716	2.1399e-05	0.2093	N/A	N/A
121500	1.723	2.1281e-05	0.232	N/A	N/A
122000	1.73	2.1163e-05	0.2178	N/A	N/A
122500	1.737	2.1045e-05	0.246	N/A	N/A
123000	1.744	2.0926e-05	0.2382	N/A	N/A
123500	1.752	2.0808e-05	0.204	N/A	N/A
124000	1.759	2.0690e-05	0.2581	N/A	N/A
124500	1.766	2.0572e-05	0.2524	N/A	N/A
125000	1.773	2.0454e-05	0.2561	N/A	N/A
125500	1.78	2.0335e-05	0.2411	N/A	N/A
126000	1.787	2.0217e-05	0.2264	N/A	N/A
126500	1.794	2.0099e-05	0.2509	N/A	N/A
127000	1.801	1.9981e-05	0.2453	N/A	N/A
127500	1.808	1.9863e-05	0.2394	N/A	N/A
128000	1.815	1.9744e-05	0.2174	N/A	N/A
128500	1.822	1.9626e-05	0.2267	N/A	N/A
129000	1.83	1.9508e-05	0.2239	N/A	N/A
129500	1.837	1.9390e-05	0.2306	N/A	N/A
130000	1.844	1.9272e-05	0.2897	N/A	N/A
130500	1.851	1.9154e-05	0.2652	N/A	N/A
131000	1.858	1.9035e-05	0.2334	N/A	N/A
131500	1.865	1.8917e-05	0.2187	N/A	N/A
132000	1.872	1.8799e-05	0.2467	N/A	N/A
132500	1.879	1.8681e-05	0.224	N/A	N/A
133000	1.886	1.8563e-05	0.2407	N/A	N/A
133500	1.893	1.8444e-05	0.2587	N/A	N/A
134000	1.9	1.8326e-05	0.2464	N/A	N/A
134500	1.908	1.8208e-05	0.2412	N/A	N/A
135000	1.915	1.8090e-05	0.2282	N/A	N/A
135500	1.922	1.7972e-05	0.2171	N/A	N/A
136000	1.929	1.7853e-05	0.2335	N/A	N/A
136500	1.936	1.7735e-05	0.2426	N/A	N/A
137000	1.943	1.7617e-05	0.2195	N/A	N/A
137500	1.95	1.7499e-05	0.2438	N/A	N/A
138000	1.957	1.7381e-05	0.2262	N/A	N/A
138500	1.964	1.7263e-05	0.2275	N/A	N/A
139000	1.971	1.7144e-05	0.2473	N/A	N/A
139500	1.978	1.7026e-05	0.2289	N/A	N/A
140000	1.986	1.6908e-05	0.2409	N/A	N/A
140500	1.993	1.6790e-05	0.2315	N/A	N/A
141000	2.0	1.6672e-05	0.2506	N/A	N/A
141020	2.0	N/A	N/A	0.307	0.9114
141500	2.007	1.6553e-05	0.1374	N/A	N/A
142000	2.014	1.6435e-05	0.1393	N/A	N/A
142500	2.021	1.6317e-05	0.1658	N/A	N/A
143000	2.028	1.6199e-05	0.1463	N/A	N/A
143500	2.035	1.6081e-05	0.1572	N/A	N/A
144000	2.042	1.5963e-05	0.1554	N/A	N/A
144500	2.049	1.5844e-05	0.1422	N/A	N/A
145000	2.056	1.5726e-05	0.1494	N/A	N/A
145500	2.064	1.5608e-05	0.1392	N/A	N/A
146000	2.071	1.5490e-05	0.166	N/A	N/A
146500	2.078	1.5372e-05	0.1702	N/A	N/A
147000	2.085	1.5253e-05	0.1702	N/A	N/A
147500	2.092	1.5135e-05	0.1524	N/A	N/A
148000	2.099	1.5017e-05	0.1637	N/A	N/A
148500	2.106	1.4899e-05	0.1443	N/A	N/A
149000	2.113	1.4781e-05	0.1502	N/A	N/A
149500	2.12	1.4662e-05	0.15	N/A	N/A
150000	2.127	1.4544e-05	0.1476	N/A	N/A
150500	2.134	1.4426e-05	0.1339	N/A	N/A
151000	2.142	1.4308e-05	0.1821	N/A	N/A
151500	2.149	1.4190e-05	0.1552	N/A	N/A
152000	2.156	1.4072e-05	0.1616	N/A	N/A
152500	2.163	1.3953e-05	0.1409	N/A	N/A
153000	2.17	1.3835e-05	0.1721	N/A	N/A
153500	2.177	1.3717e-05	0.1439	N/A	N/A
154000	2.184	1.3599e-05	0.142	N/A	N/A
154500	2.191	1.3481e-05	0.1684	N/A	N/A
155000	2.198	1.3362e-05	0.1368	N/A	N/A
155500	2.205	1.3244e-05	0.1475	N/A	N/A
156000	2.212	1.3126e-05	0.1508	N/A	N/A
156500	2.22	1.3008e-05	0.1661	N/A	N/A
157000	2.227	1.2890e-05	0.1691	N/A	N/A
157500	2.234	1.2771e-05	0.1361	N/A	N/A
158000	2.241	1.2653e-05	0.1646	N/A	N/A
158500	2.248	1.2535e-05	0.1441	N/A	N/A
159000	2.255	1.2417e-05	0.1655	N/A	N/A
159500	2.262	1.2299e-05	0.1569	N/A	N/A
160000	2.269	1.2181e-05	0.1549	N/A	N/A
160500	2.276	1.2062e-05	0.1792	N/A	N/A
161000	2.283	1.1944e-05	0.1449	N/A	N/A
161500	2.29	1.1826e-05	0.1461	N/A	N/A
162000	2.298	1.1708e-05	0.1439	N/A	N/A
162500	2.305	1.1590e-05	0.1375	N/A	N/A
163000	2.312	1.1471e-05	0.1468	N/A	N/A
163500	2.319	1.1353e-05	0.1761	N/A	N/A
164000	2.326	1.1235e-05	0.1375	N/A	N/A
164500	2.333	1.1117e-05	0.1506	N/A	N/A
165000	2.34	1.0999e-05	0.1544	N/A	N/A
165500	2.347	1.0880e-05	0.1568	N/A	N/A
166000	2.354	1.0762e-05	0.1477	N/A	N/A
166500	2.361	1.0644e-05	0.1536	N/A	N/A
167000	2.368	1.0526e-05	0.1445	N/A	N/A
167500	2.376	1.0408e-05	0.1486	N/A	N/A
168000	2.383	1.0290e-05	0.1467	N/A	N/A
168500	2.39	1.0171e-05	0.1652	N/A	N/A
169000	2.397	1.0053e-05	0.1457	N/A	N/A
169500	2.404	9.9350e-06	0.1506	N/A	N/A
170000	2.411	9.8168e-06	0.148	N/A	N/A
170500	2.418	9.6986e-06	0.1561	N/A	N/A
171000	2.425	9.5804e-06	0.1667	N/A	N/A
171500	2.432	9.4623e-06	0.1389	N/A	N/A
172000	2.439	9.3441e-06	0.1619	N/A	N/A
172500	2.446	9.2259e-06	0.1678	N/A	N/A
173000	2.454	9.1077e-06	0.1607	N/A	N/A
173500	2.461	8.9895e-06	0.1418	N/A	N/A
174000	2.468	8.8713e-06	0.1587	N/A	N/A
174500	2.475	8.7531e-06	0.137	N/A	N/A
175000	2.482	8.6349e-06	0.1655	N/A	N/A
175500	2.489	8.5168e-06	0.1423	N/A	N/A
176000	2.496	8.3986e-06	0.15	N/A	N/A
176500	2.503	8.2804e-06	0.1706	N/A	N/A
177000	2.51	8.1622e-06	0.1409	N/A	N/A
177500	2.517	8.0440e-06	0.1449	N/A	N/A
178000	2.524	7.9258e-06	0.1427	N/A	N/A
178500	2.532	7.8076e-06	0.1425	N/A	N/A
179000	2.539	7.6895e-06	0.1369	N/A	N/A
179500	2.546	7.5713e-06	0.1521	N/A	N/A
180000	2.553	7.4531e-06	0.1355	N/A	N/A
180500	2.56	7.3349e-06	0.1358	N/A	N/A
181000	2.567	7.2167e-06	0.168	N/A	N/A
181500	2.574	7.0985e-06	0.1604	N/A	N/A
182000	2.581	6.9803e-06	0.1568	N/A	N/A
182500	2.588	6.8621e-06	0.1535	N/A	N/A
183000	2.595	6.7440e-06	0.1342	N/A	N/A
183500	2.602	6.6258e-06	0.1511	N/A	N/A
184000	2.61	6.5076e-06	0.1799	N/A	N/A
184500	2.617	6.3894e-06	0.1366	N/A	N/A
185000	2.624	6.2712e-06	0.1554	N/A	N/A
185500	2.631	6.1530e-06	0.1662	N/A	N/A
186000	2.638	6.0348e-06	0.1325	N/A	N/A
186500	2.645	5.9167e-06	0.1492	N/A	N/A
187000	2.652	5.7985e-06	0.149	N/A	N/A
187500	2.659	5.6803e-06	0.133	N/A	N/A
188000	2.666	5.5621e-06	0.1321	N/A	N/A
188500	2.673	5.4439e-06	0.1539	N/A	N/A
189000	2.68	5.3257e-06	0.1272	N/A	N/A
189500	2.688	5.2075e-06	0.1332	N/A	N/A
190000	2.695	5.0893e-06	0.1508	N/A	N/A
190500	2.702	4.9712e-06	0.1518	N/A	N/A
191000	2.709	4.8530e-06	0.1374	N/A	N/A
191500	2.716	4.7348e-06	0.1621	N/A	N/A
192000	2.723	4.6166e-06	0.1612	N/A	N/A
192500	2.73	4.4984e-06	0.1396	N/A	N/A
193000	2.737	4.3802e-06	0.1354	N/A	N/A
193500	2.744	4.2620e-06	0.1398	N/A	N/A
194000	2.751	4.1439e-06	0.1264	N/A	N/A
194500	2.758	4.0257e-06	0.136	N/A	N/A
195000	2.766	3.9075e-06	0.1599	N/A	N/A
195500	2.773	3.7893e-06	0.1676	N/A	N/A
196000	2.78	3.6711e-06	0.1271	N/A	N/A
196500	2.787	3.5529e-06	0.1265	N/A	N/A
197000	2.794	3.4347e-06	0.1379	N/A	N/A
197500	2.801	3.3166e-06	0.1656	N/A	N/A
198000	2.808	3.1984e-06	0.1316	N/A	N/A
198500	2.815	3.0802e-06	0.147	N/A	N/A
199000	2.822	2.9620e-06	0.1469	N/A	N/A
199500	2.829	2.8438e-06	0.1519	N/A	N/A
200000	2.836	2.7256e-06	0.1212	N/A	N/A
200500	2.844	2.6074e-06	0.1373	N/A	N/A
201000	2.851	2.4892e-06	0.1405	N/A	N/A
201500	2.858	2.3711e-06	0.1672	N/A	N/A
202000	2.865	2.2529e-06	0.1248	N/A	N/A
202500	2.872	2.1347e-06	0.1389	N/A	N/A
203000	2.879	2.0165e-06	0.1236	N/A	N/A
203500	2.886	1.8983e-06	0.1366	N/A	N/A
204000	2.893	1.7801e-06	0.1229	N/A	N/A
204500	2.9	1.6619e-06	0.1482	N/A	N/A
205000	2.907	1.5438e-06	0.1451	N/A	N/A
205500	2.914	1.4256e-06	0.1354	N/A	N/A
206000	2.922	1.3074e-06	0.1455	N/A	N/A
206500	2.929	1.1892e-06	0.1214	N/A	N/A
207000	2.936	1.0710e-06	0.1529	N/A	N/A
207500	2.943	9.5282e-07	0.1675	N/A	N/A
208000	2.95	8.3463e-07	0.1374	N/A	N/A
208500	2.957	7.1645e-07	0.1452	N/A	N/A
209000	2.964	5.9826e-07	0.1341	N/A	N/A
209500	2.971	4.8007e-07	0.1393	N/A	N/A
210000	2.978	3.6189e-07	0.1413	N/A	N/A
210500	2.985	2.4370e-07	0.1366	N/A	N/A
211000	2.992	1.2551e-07	0.1401	N/A	N/A
211500	3.0	7.3276e-09	0.1582	N/A	N/A
211530	3.0	N/A	N/A	0.339	0.918

Framework Versions

• Transformers: 5.14.0.dev0
• PyTorch: 2.13.0+cu130