| | --- |
| | license: mit |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | - f1 |
| | - precision |
| | - recall |
| | model-index: |
| | - name: fb-data2vec-finetuned-finance-classification |
| | results: [] |
| | --- |
| | |
| | <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| | should probably proofread and complete it, then remove this comment. --> |
| |
|
| | # fb-data2vec-finetuned-finance-classification |
| |
|
| | This model is a fine-tuned version of [facebook/data2vec-text-base](https://huggingface.co/facebook/data2vec-text-base) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.8993 |
| | - Accuracy: 0.8557 |
| | - F1: 0.8563 |
| | - Precision: 0.8576 |
| | - Recall: 0.8557 |
| |
|
| | ## 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: 2e-05 |
| | - train_batch_size: 16 |
| | - eval_batch_size: 16 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 15 |
| | - mixed_precision_training: Native AMP |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
| | | No log | 1.0 | 285 | 0.6704 | 0.6680 | 0.6262 | 0.7919 | 0.6680 | |
| | | 0.6626 | 2.0 | 570 | 0.4731 | 0.8360 | 0.8350 | 0.8346 | 0.8360 | |
| | | 0.6626 | 3.0 | 855 | 0.4598 | 0.8458 | 0.8454 | 0.8452 | 0.8458 | |
| | | 0.3666 | 4.0 | 1140 | 0.4758 | 0.8360 | 0.8352 | 0.8353 | 0.8360 | |
| | | 0.3666 | 5.0 | 1425 | 0.5683 | 0.8340 | 0.8342 | 0.8353 | 0.8340 | |
| | | 0.2316 | 6.0 | 1710 | 0.6234 | 0.8419 | 0.8421 | 0.8447 | 0.8419 | |
| | | 0.2316 | 7.0 | 1995 | 0.7186 | 0.8379 | 0.8385 | 0.8395 | 0.8379 | |
| | | 0.1523 | 8.0 | 2280 | 0.7268 | 0.8439 | 0.8442 | 0.8455 | 0.8439 | |
| | | 0.0928 | 9.0 | 2565 | 0.7364 | 0.8439 | 0.8452 | 0.8494 | 0.8439 | |
| | | 0.0928 | 10.0 | 2850 | 0.7975 | 0.8478 | 0.8476 | 0.8476 | 0.8478 | |
| | | 0.054 | 11.0 | 3135 | 0.9019 | 0.8498 | 0.8509 | 0.8554 | 0.8498 | |
| | | 0.054 | 12.0 | 3420 | 0.8779 | 0.8538 | 0.8548 | 0.8578 | 0.8538 | |
| | | 0.036 | 13.0 | 3705 | 0.8914 | 0.8617 | 0.8626 | 0.8652 | 0.8617 | |
| | | 0.036 | 14.0 | 3990 | 0.8976 | 0.8538 | 0.8547 | 0.8572 | 0.8538 | |
| | | 0.0232 | 15.0 | 4275 | 0.8993 | 0.8557 | 0.8563 | 0.8576 | 0.8557 | |
| |
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| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.18.0 |
| | - Pytorch 1.11.0+cu113 |
| | - Datasets 2.1.0 |
| | - Tokenizers 0.12.1 |
| |
|
