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--- |
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base_model: RefalMachine/mistral_extended_darulm_20_05_24_part1-2_32000_bpe_mean_init_03_07_24 |
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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: mistral_extended_darulm_20_05_24_part1-2_32000_bpe_part1_lr2e5_bs256 |
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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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# mistral_extended_darulm_20_05_24_part1-2_32000_bpe_part1_lr2e5_bs256 |
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This model is a fine-tuned version of [RefalMachine/mistral_extended_darulm_20_05_24_part1-2_32000_bpe_mean_init_03_07_24](https://huggingface.co/RefalMachine/mistral_extended_darulm_20_05_24_part1-2_32000_bpe_mean_init_03_07_24) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.2338 |
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- Accuracy: 0.5418 |
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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: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 32 |
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- total_train_batch_size: 128 |
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- total_eval_batch_size: 128 |
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- optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-05 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 100 |
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- num_epochs: 1.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:| |
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| 2.6021 | 0.09 | 2000 | 2.3285 | 0.5305 | |
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| 2.5355 | 0.18 | 4000 | 2.2744 | 0.5365 | |
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| 2.5063 | 0.27 | 6000 | 2.2538 | 0.5391 | |
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| 2.4939 | 0.36 | 8000 | 2.2441 | 0.5402 | |
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| 2.463 | 0.45 | 10000 | 2.2385 | 0.5410 | |
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| 2.4559 | 0.54 | 12000 | 2.2359 | 0.5414 | |
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| 2.5186 | 0.63 | 14000 | 2.2347 | 0.5415 | |
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| 2.4755 | 0.73 | 16000 | 2.2340 | 0.5416 | |
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| 2.4813 | 0.82 | 18000 | 2.2338 | 0.5417 | |
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| 2.4797 | 0.91 | 20000 | 2.2338 | 0.5418 | |
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| 2.4525 | 1.0 | 22000 | 2.2338 | 0.5418 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.3.0a0+6ddf5cf85e.nv24.04 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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