README.md

metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - stereoset
metrics:
  - accuracy
model-index:
  - name: bert-base-uncased_stereoset_finetuned
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: stereoset
          type: stereoset
          config: intersentence
          split: validation
          args: intersentence
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.7260596546310832

bert-base-uncased_stereoset_finetuned

This model is a fine-tuned version of bert-base-uncased on the stereoset dataset. It achieves the following results on the evaluation set:

• Loss: 1.3464
• Accuracy: 0.7261

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 5e-05
• train_batch_size: 128
• eval_batch_size: 64
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	0.21	5	0.6832	0.5565
No log	0.42	10	0.6945	0.4741
No log	0.62	15	0.6659	0.6224
No log	0.83	20	0.6337	0.6758
No log	1.04	25	0.6019	0.6695
No log	1.25	30	0.5797	0.7096
No log	1.46	35	0.5562	0.7166
No log	1.67	40	0.5497	0.7363
No log	1.88	45	0.5382	0.7418
No log	2.08	50	0.5356	0.7418
No log	2.29	55	0.5690	0.7316
No log	2.5	60	0.5778	0.7418
No log	2.71	65	0.5695	0.7386
No log	2.92	70	0.5765	0.7386
No log	3.12	75	0.6079	0.7363
No log	3.33	80	0.6919	0.7370
No log	3.54	85	0.7396	0.7339
No log	3.75	90	0.7109	0.7339
No log	3.96	95	0.7246	0.7308
No log	4.17	100	0.7502	0.7292
No log	4.38	105	0.8222	0.7331
No log	4.58	110	0.8508	0.7268
No log	4.79	115	0.8995	0.7378
No log	5.0	120	0.8797	0.7323
No log	5.21	125	0.9254	0.7370
No log	5.42	130	0.9863	0.7292
No log	5.62	135	1.0044	0.7198
No log	5.83	140	1.0236	0.7339
No log	6.04	145	1.0705	0.7355
No log	6.25	150	1.0734	0.7323
No log	6.46	155	1.1066	0.7300
No log	6.67	160	1.1166	0.7292
No log	6.88	165	1.1258	0.7370
No log	7.08	170	1.1972	0.7300
No log	7.29	175	1.1682	0.7268
No log	7.5	180	1.2221	0.7166
No log	7.71	185	1.2813	0.7151
No log	7.92	190	1.3180	0.7214
No log	8.12	195	1.3224	0.7166
No log	8.33	200	1.3252	0.7135
No log	8.54	205	1.3205	0.7221
No log	8.75	210	1.3266	0.7245
No log	8.96	215	1.3318	0.7206
No log	9.17	220	1.3345	0.7237
No log	9.38	225	1.3378	0.7245
No log	9.58	230	1.3422	0.7261
No log	9.79	235	1.3453	0.7261
No log	10.0	240	1.3464	0.7261

Framework versions

• Transformers 4.26.1
• Pytorch 1.13.1
• Datasets 2.9.0
• Tokenizers 0.13.2