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--- |
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license: mit |
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base_model: intfloat/multilingual-e5-small |
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tags: |
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- generated_from_trainer |
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metrics: |
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- f1 |
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- accuracy |
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model-index: |
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- name: multi-e5-small_lmd-comments_v1 |
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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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# multi-e5-small_lmd-comments_v1 |
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This model is a fine-tuned version of [intfloat/multilingual-e5-small](https://huggingface.co/intfloat/multilingual-e5-small) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9808 |
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- F1: 0.7036 |
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- Accuracy: 0.7122 |
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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: 8 |
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- eval_batch_size: 8 |
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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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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 2 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:--------:| |
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| 1.0969 | 0.04 | 100 | 1.0991 | 0.4109 | 0.4964 | |
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| 1.0764 | 0.08 | 200 | 1.0768 | 0.5217 | 0.5971 | |
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| 0.955 | 0.12 | 300 | 0.9313 | 0.5802 | 0.6691 | |
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| 0.8137 | 0.17 | 400 | 0.8927 | 0.5864 | 0.6475 | |
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| 0.7837 | 0.21 | 500 | 0.8711 | 0.6238 | 0.6475 | |
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| 0.7234 | 0.25 | 600 | 0.9953 | 0.5641 | 0.6475 | |
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| 0.6983 | 0.29 | 700 | 0.9111 | 0.6226 | 0.6475 | |
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| 0.6574 | 0.33 | 800 | 0.8557 | 0.6686 | 0.6835 | |
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| 0.6653 | 0.37 | 900 | 0.7925 | 0.7087 | 0.7122 | |
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| 0.6444 | 0.41 | 1000 | 0.8338 | 0.7056 | 0.7122 | |
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| 0.6155 | 0.46 | 1100 | 0.8339 | 0.7257 | 0.7338 | |
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| 0.5726 | 0.5 | 1200 | 0.8078 | 0.7140 | 0.7194 | |
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| 0.6279 | 0.54 | 1300 | 0.9534 | 0.6917 | 0.7050 | |
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| 0.6083 | 0.58 | 1400 | 0.9515 | 0.6914 | 0.7050 | |
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| 0.5525 | 0.62 | 1500 | 0.9281 | 0.6846 | 0.7050 | |
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| 0.6849 | 0.66 | 1600 | 0.8352 | 0.6917 | 0.7050 | |
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| 0.5924 | 0.7 | 1700 | 1.0702 | 0.6602 | 0.6906 | |
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| 0.5614 | 0.75 | 1800 | 0.9689 | 0.6801 | 0.6978 | |
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| 0.5936 | 0.79 | 1900 | 1.0179 | 0.6896 | 0.7050 | |
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| 0.5582 | 0.83 | 2000 | 0.8858 | 0.7320 | 0.7410 | |
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| 0.5479 | 0.87 | 2100 | 0.9373 | 0.7030 | 0.7122 | |
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| 0.6278 | 0.91 | 2200 | 0.8694 | 0.6858 | 0.6978 | |
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| 0.4819 | 0.95 | 2300 | 0.9440 | 0.7074 | 0.7194 | |
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| 0.5425 | 0.99 | 2400 | 1.0661 | 0.6765 | 0.6906 | |
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| 0.5804 | 1.04 | 2500 | 0.8904 | 0.7189 | 0.7266 | |
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| 0.5025 | 1.08 | 2600 | 1.0105 | 0.6886 | 0.7050 | |
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| 0.5148 | 1.12 | 2700 | 0.9934 | 0.7076 | 0.7194 | |
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| 0.5359 | 1.16 | 2800 | 0.9249 | 0.7291 | 0.7410 | |
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| 0.5002 | 1.2 | 2900 | 0.7503 | 0.7047 | 0.7050 | |
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| 0.4563 | 1.24 | 3000 | 0.8149 | 0.7230 | 0.7266 | |
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| 0.4837 | 1.28 | 3100 | 0.8956 | 0.7125 | 0.7194 | |
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| 0.4486 | 1.33 | 3200 | 0.9013 | 0.7110 | 0.7194 | |
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| 0.4721 | 1.37 | 3300 | 1.0545 | 0.7142 | 0.7266 | |
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| 0.5482 | 1.41 | 3400 | 1.0139 | 0.7014 | 0.7122 | |
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| 0.4488 | 1.45 | 3500 | 0.9427 | 0.7162 | 0.7266 | |
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| 0.4859 | 1.49 | 3600 | 1.1337 | 0.7074 | 0.7194 | |
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| 0.504 | 1.53 | 3700 | 1.0299 | 0.7178 | 0.7266 | |
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| 0.4555 | 1.57 | 3800 | 0.8830 | 0.7273 | 0.7338 | |
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| 0.502 | 1.62 | 3900 | 1.0340 | 0.7142 | 0.7266 | |
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| 0.5131 | 1.66 | 4000 | 1.0997 | 0.7031 | 0.7194 | |
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| 0.5208 | 1.7 | 4100 | 1.0845 | 0.7025 | 0.7194 | |
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| 0.4329 | 1.74 | 4200 | 1.0553 | 0.7132 | 0.7266 | |
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| 0.4612 | 1.78 | 4300 | 1.0458 | 0.7074 | 0.7194 | |
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| 0.4857 | 1.82 | 4400 | 0.9425 | 0.7120 | 0.7194 | |
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| 0.4986 | 1.86 | 4500 | 0.9965 | 0.7237 | 0.7338 | |
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| 0.4066 | 1.91 | 4600 | 0.9520 | 0.7041 | 0.7122 | |
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| 0.4638 | 1.95 | 4700 | 0.9558 | 0.6979 | 0.7050 | |
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| 0.4541 | 1.99 | 4800 | 0.9808 | 0.7036 | 0.7122 | |
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### Framework versions |
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- Transformers 4.38.1 |
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- Pytorch 2.1.2 |
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- Datasets 2.1.0 |
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- Tokenizers 0.15.2 |
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