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SmolLM-1.7B-Instruct_fsdp_qlora_nf4_adapter-plaba

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README.md ADDED
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+ ---
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+ library_name: peft
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+ tags:
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+ - trl
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+ - sft
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+ - generated_from_trainer
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+ base_model: dmariko/SmolLM-1.7B-Instruct_qlora_nf4_merged
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+ datasets:
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+ - generator
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+ model-index:
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+ - name: SmolLM_1_7B_Instruct_qlora_nf4-plaba
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+ results: []
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+ ---
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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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+
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+ # SmolLM_1_7B_Instruct_qlora_nf4-plaba
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+
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+ This model is a fine-tuned version of [dmariko/SmolLM-1.7B-Instruct_qlora_nf4_merged](https://huggingface.co/dmariko/SmolLM-1.7B-Instruct_qlora_nf4_merged) on the generator dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.6099
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 0.001
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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: 16
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 256
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+ - total_eval_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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+ - num_epochs: 20
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:-----:|:----:|:---------------:|
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+ | No log | 0.8 | 1 | 1.7411 |
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+ | No log | 1.6 | 2 | 1.7359 |
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+ | No log | 2.4 | 3 | 1.7081 |
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+ | No log | 4.0 | 5 | 1.6632 |
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+ | No log | 4.8 | 6 | 1.6608 |
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+ | No log | 5.6 | 7 | 1.6495 |
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+ | No log | 6.4 | 8 | 1.6376 |
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+ | 1.6842 | 8.0 | 10 | 1.6228 |
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+ | 1.6842 | 8.8 | 11 | 1.6187 |
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+ | 1.6842 | 9.6 | 12 | 1.6161 |
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+ | 1.6842 | 10.4 | 13 | 1.6142 |
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+ | 1.6842 | 12.0 | 15 | 1.6116 |
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+ | 1.6842 | 12.8 | 16 | 1.6108 |
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+ | 1.6842 | 13.6 | 17 | 1.6103 |
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+ | 1.6842 | 14.4 | 18 | 1.6100 |
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+ | 1.6057 | 16.0 | 20 | 1.6099 |
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.10.0
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+ - Transformers 4.40.0
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+ - Pytorch 2.1.0
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+ - Datasets 2.18.0
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+ - Tokenizers 0.19.1
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