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--- |
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base_model: mikhail-panzo/zlm_b128_le4_s12000 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: zlm-fil_b64_le5_s8000 |
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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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# zlm-fil_b64_le5_s8000 |
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This model is a fine-tuned version of [mikhail-panzo/zlm_b128_le4_s12000](https://huggingface.co/mikhail-panzo/zlm_b128_le4_s12000) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4077 |
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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: 1e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 64 |
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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: 2000 |
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- training_steps: 8000 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:--------:|:----:|:---------------:| |
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| 0.5541 | 21.7391 | 500 | 0.4977 | |
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| 0.4931 | 43.4783 | 1000 | 0.4529 | |
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| 0.4695 | 65.2174 | 1500 | 0.4330 | |
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| 0.4518 | 86.9565 | 2000 | 0.4230 | |
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| 0.4442 | 108.6957 | 2500 | 0.4179 | |
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| 0.4344 | 130.4348 | 3000 | 0.4135 | |
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| 0.4318 | 152.1739 | 3500 | 0.4111 | |
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| 0.4201 | 173.9130 | 4000 | 0.4110 | |
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| 0.4185 | 195.6522 | 4500 | 0.4091 | |
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| 0.4153 | 217.3913 | 5000 | 0.4097 | |
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| 0.414 | 239.1304 | 5500 | 0.4069 | |
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| 0.4113 | 260.8696 | 6000 | 0.4080 | |
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| 0.4133 | 282.6087 | 6500 | 0.4073 | |
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| 0.4095 | 304.3478 | 7000 | 0.4059 | |
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| 0.4129 | 326.0870 | 7500 | 0.4083 | |
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| 0.4035 | 347.8261 | 8000 | 0.4077 | |
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### Framework versions |
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- Transformers 4.41.0.dev0 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.19.0 |
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- Tokenizers 0.19.1 |
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