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