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--- |
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license: other |
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library_name: peft |
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tags: |
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- generated_from_trainer |
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base_model: Qwen/Qwen1.5-7B |
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metrics: |
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- accuracy |
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model-index: |
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- name: lex_glue |
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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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# lex_glue |
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This model is a fine-tuned version of [Qwen/Qwen1.5-7B](https://huggingface.co/Qwen/Qwen1.5-7B) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.6125 |
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- Accuracy: 0.5507 |
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- F1 Macro: 0.4051 |
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- F1 Micro: 0.5507 |
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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: 5e-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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- distributed_type: multi-GPU |
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- num_devices: 2 |
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- total_train_batch_size: 32 |
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- total_eval_batch_size: 32 |
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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: 3.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | F1 Micro | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:--------:| |
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| 2.3973 | 0.32 | 50 | 2.1948 | 0.38 | 0.1677 | 0.38 | |
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| 1.6438 | 0.64 | 100 | 1.8118 | 0.4271 | 0.2466 | 0.4271 | |
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| 1.7379 | 0.96 | 150 | 1.7119 | 0.4771 | 0.2704 | 0.4771 | |
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| 1.409 | 1.27 | 200 | 1.7488 | 0.4871 | 0.2973 | 0.4871 | |
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| 1.2443 | 1.59 | 250 | 1.6798 | 0.5364 | 0.3334 | 0.5364 | |
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| 1.1602 | 1.91 | 300 | 1.6132 | 0.5243 | 0.3573 | 0.5243 | |
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| 1.1191 | 2.23 | 350 | 1.6507 | 0.5386 | 0.3914 | 0.5386 | |
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| 0.8907 | 2.55 | 400 | 1.6125 | 0.5507 | 0.4051 | 0.5507 | |
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| 0.9012 | 2.87 | 450 | 1.6445 | 0.5529 | 0.4088 | 0.5529 | |
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### Framework versions |
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- PEFT 0.9.0 |
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- Transformers 4.39.0.dev0 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
