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README.md
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Quantization made by Richard Erkhov.
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[Github](https://github.com/RichardErkhov)
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[Discord](https://discord.gg/pvy7H8DZMG)
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[Request more models](https://github.com/RichardErkhov/quant_request)
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opt-350m_fine_lr5e-05_bs4_epoch20_wd0.01 - AWQ
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- Model creator: https://huggingface.co/jysssacc/
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- Original model: https://huggingface.co/jysssacc/opt-350m_fine_lr5e-05_bs4_epoch20_wd0.01/
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Original model description:
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---
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license: other
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base_model: facebook/opt-350m
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tags:
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- generated_from_trainer
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model-index:
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- name: opt-350m_fine_lr5e-05_bs4_epoch20_wd0.01
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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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# opt-350m_fine_lr5e-05_bs4_epoch20_wd0.01
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This model is a fine-tuned version of [facebook/opt-350m](https://huggingface.co/facebook/opt-350m) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 6.4402
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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: 4
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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_steps: 500
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- num_epochs: 20
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:----:|:---------------:|
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| 3.6861 | 1.0 | 157 | 3.5351 |
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| 2.8315 | 2.0 | 314 | 3.7727 |
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| 1.9912 | 3.0 | 471 | 4.1666 |
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| 1.4737 | 4.0 | 628 | 4.4532 |
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| 1.1977 | 5.0 | 785 | 4.9565 |
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| 0.8678 | 6.0 | 942 | 4.9429 |
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| 0.8014 | 7.0 | 1099 | 5.3148 |
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| 0.685 | 8.0 | 1256 | 5.4586 |
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| 0.6793 | 9.0 | 1413 | 5.3924 |
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| 0.6246 | 10.0 | 1570 | 5.6821 |
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| 0.5972 | 11.0 | 1727 | 5.8316 |
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| 0.5604 | 12.0 | 1884 | 5.8977 |
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| 0.5404 | 13.0 | 2041 | 6.0070 |
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| 0.5375 | 14.0 | 2198 | 5.9317 |
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| 0.5035 | 15.0 | 2355 | 6.1104 |
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| 0.5088 | 16.0 | 2512 | 6.2142 |
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| 0.4827 | 17.0 | 2669 | 6.1858 |
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| 0.4744 | 18.0 | 2826 | 6.3306 |
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| 0.4641 | 19.0 | 2983 | 6.3937 |
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| 0.4531 | 20.0 | 3140 | 6.4402 |
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### Framework versions
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- Transformers 4.36.2
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- Pytorch 2.0.1
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- Datasets 2.16.1
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- Tokenizers 0.15.0
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