Realgon/N_bert_sst5_padding100model

1---2license: apache-2.03base_model: bert-base-uncased4tags:5- generated_from_trainer6metrics:7- accuracy8model-index:9- name: N_bert_sst5_padding100model10  results: []11---12 13<!-- This model card has been generated automatically according to the information the Trainer had access to. You14should probably proofread and complete it, then remove this comment. -->15 16# N_bert_sst5_padding100model17 18This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.19It achieves the following results on the evaluation set:20- Loss: 4.044121- Accuracy: 0.524922 23## Model description24 25More information needed26 27## Intended uses & limitations28 29More information needed30 31## Training and evaluation data32 33More information needed34 35## Training procedure36 37### Training hyperparameters38 39The following hyperparameters were used during training:40- learning_rate: 2e-0541- train_batch_size: 1642- eval_batch_size: 1643- seed: 4244- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-0845- lr_scheduler_type: linear46- num_epochs: 2047 48### Training results49 50| Training Loss | Epoch | Step  | Validation Loss | Accuracy |51|:-------------:|:-----:|:-----:|:---------------:|:--------:|52| 1.3098        | 1.0   | 534   | 1.3057          | 0.4339   |53| 0.9919        | 2.0   | 1068  | 1.0863          | 0.5326   |54| 0.7654        | 3.0   | 1602  | 1.1988          | 0.5231   |55| 0.593         | 4.0   | 2136  | 1.3832          | 0.5244   |56| 0.4256        | 5.0   | 2670  | 1.6810          | 0.5154   |57| 0.313         | 6.0   | 3204  | 1.9396          | 0.5154   |58| 0.2169        | 7.0   | 3738  | 2.2859          | 0.5140   |59| 0.1745        | 8.0   | 4272  | 2.6011          | 0.5163   |60| 0.1521        | 9.0   | 4806  | 2.7484          | 0.5181   |61| 0.1278        | 10.0  | 5340  | 3.0932          | 0.5281   |62| 0.0993        | 11.0  | 5874  | 3.2683          | 0.5181   |63| 0.097         | 12.0  | 6408  | 3.4021          | 0.5217   |64| 0.0629        | 13.0  | 6942  | 3.7096          | 0.5258   |65| 0.0437        | 14.0  | 7476  | 3.7275          | 0.5235   |66| 0.0298        | 15.0  | 8010  | 3.7627          | 0.5290   |67| 0.0257        | 16.0  | 8544  | 3.8717          | 0.5276   |68| 0.0175        | 17.0  | 9078  | 3.9446          | 0.5213   |69| 0.0174        | 18.0  | 9612  | 3.9703          | 0.5226   |70| 0.0101        | 19.0  | 10146 | 4.0437          | 0.5222   |71| 0.007         | 20.0  | 10680 | 4.0441          | 0.5249   |72 73 74### Framework versions75 76- Transformers 4.33.277- Pytorch 2.0.1+cu11778- Datasets 2.14.579- Tokenizers 0.13.380