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--- |
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license: llama3 |
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base_model: meta-llama/Meta-Llama-3-8B |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: MSc_llama3_finetuned_model_secondData |
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results: [] |
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library_name: peft |
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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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# MSc_llama3_finetuned_model_secondData |
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This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9224 |
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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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The following `bitsandbytes` quantization config was used during training: |
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- quant_method: bitsandbytes |
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- _load_in_8bit: False |
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- _load_in_4bit: True |
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- llm_int8_threshold: 6.0 |
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- llm_int8_skip_modules: None |
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- llm_int8_enable_fp32_cpu_offload: False |
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- llm_int8_has_fp16_weight: False |
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- bnb_4bit_quant_type: nf4 |
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- bnb_4bit_use_double_quant: True |
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- bnb_4bit_compute_dtype: bfloat16 |
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- load_in_4bit: True |
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- load_in_8bit: False |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 3e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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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: cosine |
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- lr_scheduler_warmup_ratio: 0.03 |
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- training_steps: 250 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 3.791 | 1.33 | 10 | 3.6476 | |
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| 3.2811 | 2.67 | 20 | 2.9195 | |
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| 2.3899 | 4.0 | 30 | 1.8723 | |
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| 1.5443 | 5.33 | 40 | 1.3519 | |
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| 1.2394 | 6.67 | 50 | 1.1884 | |
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| 1.1162 | 8.0 | 60 | 1.1023 | |
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| 1.0377 | 9.33 | 70 | 1.0551 | |
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| 0.9831 | 10.67 | 80 | 1.0228 | |
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| 0.9476 | 12.0 | 90 | 0.9988 | |
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| 0.9032 | 13.33 | 100 | 0.9850 | |
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| 0.8799 | 14.67 | 110 | 0.9668 | |
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| 0.8581 | 16.0 | 120 | 0.9503 | |
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| 0.8315 | 17.33 | 130 | 0.9457 | |
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| 0.8077 | 18.67 | 140 | 0.9422 | |
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| 0.7921 | 20.0 | 150 | 0.9362 | |
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| 0.7752 | 21.33 | 160 | 0.9318 | |
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| 0.7614 | 22.67 | 170 | 0.9306 | |
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| 0.7559 | 24.0 | 180 | 0.9233 | |
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| 0.7441 | 25.33 | 190 | 0.9237 | |
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| 0.7345 | 26.67 | 200 | 0.9237 | |
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| 0.7341 | 28.0 | 210 | 0.9205 | |
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| 0.7288 | 29.33 | 220 | 0.9195 | |
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| 0.7237 | 30.67 | 230 | 0.9219 | |
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| 0.7255 | 32.0 | 240 | 0.9210 | |
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| 0.7273 | 33.33 | 250 | 0.9224 | |
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### Framework versions |
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- PEFT 0.4.0 |
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- Transformers 4.38.2 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.13.1 |
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- Tokenizers 0.15.2 |
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