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--- |
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license: apache-2.0 |
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base_model: distilbert-base-uncased |
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tags: |
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- generated_from_trainer |
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datasets: |
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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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- task: |
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name: Text Classification |
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type: text-classification |
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dataset: |
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name: financial_phrasebank |
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type: financial_phrasebank |
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config: sentences_50agree |
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split: train |
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args: sentences_50agree |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.7045454545454546 |
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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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# distilbert-finance |
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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: 1.7474 |
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- Accuracy: 0.7045 |
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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: 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: cosine |
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- num_epochs: 10 |
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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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| 0.6755 | 0.33 | 20 | 1.4948 | 0.3709 | |
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| 0.4585 | 0.66 | 40 | 0.9705 | 0.6147 | |
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| 0.4267 | 0.98 | 60 | 1.2383 | 0.6012 | |
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| 0.3298 | 1.31 | 80 | 1.0040 | 0.5764 | |
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| 0.2955 | 1.64 | 100 | 1.4078 | 0.4845 | |
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| 0.2521 | 1.97 | 120 | 1.2183 | 0.5702 | |
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| 0.1614 | 2.3 | 140 | 1.4761 | 0.6570 | |
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| 0.1842 | 2.62 | 160 | 1.8172 | 0.6002 | |
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| 0.2124 | 2.95 | 180 | 0.9596 | 0.7211 | |
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| 0.1016 | 3.28 | 200 | 1.3150 | 0.6952 | |
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| 0.0949 | 3.61 | 220 | 1.5779 | 0.6498 | |
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| 0.102 | 3.93 | 240 | 1.9178 | 0.5775 | |
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| 0.0542 | 4.26 | 260 | 2.0914 | 0.6074 | |
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| 0.059 | 4.59 | 280 | 1.7965 | 0.6560 | |
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| 0.0578 | 4.92 | 300 | 2.0358 | 0.5279 | |
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| 0.0335 | 5.25 | 320 | 1.5614 | 0.6829 | |
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| 0.0414 | 5.57 | 340 | 1.8126 | 0.6405 | |
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| 0.0263 | 5.9 | 360 | 1.4405 | 0.6798 | |
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| 0.0257 | 6.23 | 380 | 1.0230 | 0.7417 | |
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| 0.0123 | 6.56 | 400 | 1.9126 | 0.6818 | |
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| 0.0218 | 6.89 | 420 | 1.8622 | 0.6860 | |
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| 0.0063 | 7.21 | 440 | 2.0173 | 0.6705 | |
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| 0.014 | 7.54 | 460 | 1.9129 | 0.6870 | |
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| 0.0037 | 7.87 | 480 | 1.7622 | 0.7035 | |
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| 0.0155 | 8.2 | 500 | 1.7379 | 0.7004 | |
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| 0.0087 | 8.52 | 520 | 1.7150 | 0.6994 | |
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| 0.0055 | 8.85 | 540 | 1.7286 | 0.7025 | |
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| 0.0051 | 9.18 | 560 | 1.7418 | 0.7014 | |
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| 0.0049 | 9.51 | 580 | 1.7468 | 0.7035 | |
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| 0.0056 | 9.84 | 600 | 1.7474 | 0.7045 | |
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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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