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--- |
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license: mit |
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base_model: microsoft/xtremedistil-l6-h256-uncased |
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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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model-index: |
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- name: xtremedistil-l6-h256-uncased-zeroshot-v1.1-none |
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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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# xtremedistil-l6-h256-uncased-zeroshot-v1.1-none |
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This model is a fine-tuned version of [microsoft/xtremedistil-l6-h256-uncased](https://huggingface.co/microsoft/xtremedistil-l6-h256-uncased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1992 |
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- F1 Macro: 0.5455 |
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- F1 Micro: 0.6194 |
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- Accuracy Balanced: 0.5960 |
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- Accuracy: 0.6194 |
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- Precision Macro: 0.5566 |
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- Recall Macro: 0.5960 |
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- Precision Micro: 0.6194 |
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- Recall Micro: 0.6194 |
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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: 32 |
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- eval_batch_size: 128 |
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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: 0.06 |
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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1 Micro | Accuracy Balanced | Accuracy | Precision Macro | Recall Macro | Precision Micro | Recall Micro | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:--------:|:-----------------:|:--------:|:---------------:|:------------:|:---------------:|:------------:| |
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| 0.3056 | 1.0 | 30790 | 0.4634 | 0.7791 | 0.8013 | 0.7757 | 0.8013 | 0.7832 | 0.7757 | 0.8013 | 0.8013 | |
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| 0.2847 | 2.0 | 61580 | 0.4656 | 0.7826 | 0.8040 | 0.7797 | 0.8040 | 0.7859 | 0.7797 | 0.8040 | 0.8040 | |
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| 0.2618 | 3.0 | 92370 | 0.4774 | 0.7848 | 0.8045 | 0.7841 | 0.8045 | 0.7856 | 0.7841 | 0.8045 | 0.8045 | |
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### Framework versions |
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- Transformers 4.33.3 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.14.7 |
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- Tokenizers 0.13.3 |
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