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update model card README.md
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README.md
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- financial_phrasebank
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metrics:
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- accuracy
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- f1
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model-index:
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- name: distilbert-finance
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results:
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.
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- name: F1
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type: f1
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value: 0.6955188246097337
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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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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the financial_phrasebank dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.
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- Accuracy: 0.
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- F1: 0.6955
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate:
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- train_batch_size:
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- eval_batch_size:
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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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### Training results
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### Framework versions
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- Transformers 4.31.0
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- Pytorch 2.0.1+cu117
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- Datasets 2.14.
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- Tokenizers 0.13.3
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- financial_phrasebank
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metrics:
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- accuracy
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model-index:
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- name: distilbert-finance
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results:
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.6993801652892562
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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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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the financial_phrasebank dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.5012
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- Accuracy: 0.6994
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.0002
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- train_batch_size: 64
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- eval_batch_size: 64
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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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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 0.6623 | 0.33 | 20 | 1.4571 | 0.3709 |
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| 0.424 | 0.66 | 40 | 1.0223 | 0.6126 |
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| 0.4282 | 0.98 | 60 | 1.0824 | 0.6343 |
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| 0.3126 | 1.31 | 80 | 0.9320 | 0.6612 |
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| 0.2464 | 1.64 | 100 | 0.8817 | 0.6963 |
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| 0.2677 | 1.97 | 120 | 0.9278 | 0.6994 |
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| 0.1221 | 2.3 | 140 | 1.7929 | 0.6322 |
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| 0.1392 | 2.62 | 160 | 1.0517 | 0.7004 |
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| 0.1982 | 2.95 | 180 | 1.0295 | 0.6684 |
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| 0.1055 | 3.28 | 200 | 0.9028 | 0.7252 |
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| 0.0704 | 3.61 | 220 | 1.6708 | 0.6188 |
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| 0.0962 | 3.93 | 240 | 1.1233 | 0.7200 |
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| 0.0356 | 4.26 | 260 | 1.1614 | 0.7603 |
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| 0.0553 | 4.59 | 280 | 1.1362 | 0.7149 |
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| 0.0665 | 4.92 | 300 | 1.2905 | 0.6529 |
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| 0.0441 | 5.25 | 320 | 1.5180 | 0.6932 |
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| 0.0425 | 5.57 | 340 | 1.3501 | 0.6808 |
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| 0.0267 | 5.9 | 360 | 1.2062 | 0.7159 |
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| 0.0198 | 6.23 | 380 | 1.3289 | 0.7262 |
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| 0.0228 | 6.56 | 400 | 1.6142 | 0.6694 |
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| 0.0209 | 6.89 | 420 | 1.8779 | 0.6147 |
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| 0.0295 | 7.21 | 440 | 1.1260 | 0.6994 |
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| 0.0138 | 7.54 | 460 | 1.4690 | 0.6756 |
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| 0.0091 | 7.87 | 480 | 1.2774 | 0.7035 |
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| 0.0094 | 8.2 | 500 | 1.8177 | 0.6384 |
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| 0.0075 | 8.52 | 520 | 1.3794 | 0.7004 |
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| 0.0079 | 8.85 | 540 | 1.4167 | 0.6994 |
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| 0.0039 | 9.18 | 560 | 1.4824 | 0.6921 |
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| 0.0023 | 9.51 | 580 | 1.5161 | 0.6932 |
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| 0.005 | 9.84 | 600 | 1.5012 | 0.6994 |
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### Framework versions
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- Transformers 4.31.0
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- Pytorch 2.0.1+cu117
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- Datasets 2.14.4
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- Tokenizers 0.13.3
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