Realgon/N_bert_twitterfin_padding50model

1---2license: apache-2.03base_model: bert-base-uncased4tags:5- generated_from_trainer6metrics:7- accuracy8model-index:9- name: N_bert_twitterfin_padding50model10  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_twitterfin_padding50model17 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: 1.000421- Accuracy: 0.887422 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| 0.6211        | 1.0   | 597   | 0.3962          | 0.8492   |53| 0.3341        | 2.0   | 1194  | 0.3131          | 0.8911   |54| 0.2233        | 3.0   | 1791  | 0.4254          | 0.8874   |55| 0.1535        | 4.0   | 2388  | 0.6356          | 0.8819   |56| 0.1104        | 5.0   | 2985  | 0.6353          | 0.8886   |57| 0.0362        | 6.0   | 3582  | 0.7047          | 0.8886   |58| 0.0337        | 7.0   | 4179  | 0.7146          | 0.8865   |59| 0.02          | 8.0   | 4776  | 0.7171          | 0.8869   |60| 0.0271        | 9.0   | 5373  | 0.7534          | 0.8907   |61| 0.0173        | 10.0  | 5970  | 0.8021          | 0.8949   |62| 0.0148        | 11.0  | 6567  | 0.8200          | 0.8894   |63| 0.0073        | 12.0  | 7164  | 0.9640          | 0.8823   |64| 0.0082        | 13.0  | 7761  | 0.9143          | 0.8823   |65| 0.0093        | 14.0  | 8358  | 0.9854          | 0.8827   |66| 0.0058        | 15.0  | 8955  | 0.9301          | 0.8911   |67| 0.0036        | 16.0  | 9552  | 0.9559          | 0.8844   |68| 0.003         | 17.0  | 10149 | 0.9667          | 0.8915   |69| 0.0019        | 18.0  | 10746 | 0.9877          | 0.8915   |70| 0.0023        | 19.0  | 11343 | 0.9900          | 0.8878   |71| 0.0027        | 20.0  | 11940 | 1.0004          | 0.8874   |72 73 74### Framework versions75 76- Transformers 4.33.277- Pytorch 2.0.1+cu11778- Datasets 2.14.579- Tokenizers 0.13.380