tuanna08go
commited on
End of training
Browse files- README.md +11 -17
- adapter_model.bin +1 -1
README.md
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@@ -47,7 +47,7 @@ flash_attention: false
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fp16: null
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fsdp: null
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fsdp_config: null
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gradient_accumulation_steps:
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gradient_checkpointing: false
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group_by_length: false
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hub_model_id: tuanna08go/decda85a-cc80-403f-8f61-2d4405578f06
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load_in_4bit: false
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load_in_8bit: false
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local_rank: null
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logging_steps:
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lora_alpha: 16
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lora_dropout: 0.05
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lora_fan_in_fan_out: null
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lora_r: 8
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lora_target_linear: true
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lr_scheduler: cosine
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max_steps:
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micro_batch_size:
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mlflow_experiment_name: /tmp/75e2dfb45725a08d_train_data.json
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model_type: AutoModelForCausalLM
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num_epochs: 1
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@@ -91,7 +91,7 @@ wandb_name: decda85a-cc80-403f-8f61-2d4405578f06
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wandb_project: Gradients-On-Demand
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wandb_run: your_name
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wandb_runid: decda85a-cc80-403f-8f61-2d4405578f06
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warmup_steps:
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weight_decay: 0.0
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xformers_attention: null
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# decda85a-cc80-403f-8f61-2d4405578f06
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This model is a fine-tuned version of [unsloth/Qwen2.5-Math-1.5B](https://huggingface.co/unsloth/Qwen2.5-Math-1.5B) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: nan
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## Model description
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The following hyperparameters were used during training:
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- learning_rate: 0.0001
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- train_batch_size:
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- eval_batch_size:
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- seed: 42
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- gradient_accumulation_steps:
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- total_train_batch_size:
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- optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_steps: 2
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- training_steps:
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:------:|:----:|:---------------:|
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| No log | 0.
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| No log | 0.2243 | 3 | nan |
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| No log | 0.4486 | 6 | nan |
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| No log | 0.6729 | 9 | nan |
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| 0.0 | 0.8972 | 12 | nan |
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### Framework versions
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fp16: null
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fsdp: null
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fsdp_config: null
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gradient_accumulation_steps: 4
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gradient_checkpointing: false
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group_by_length: false
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hub_model_id: tuanna08go/decda85a-cc80-403f-8f61-2d4405578f06
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load_in_4bit: false
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load_in_8bit: false
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local_rank: null
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logging_steps: 5
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lora_alpha: 16
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lora_dropout: 0.05
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lora_fan_in_fan_out: null
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lora_r: 8
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lora_target_linear: true
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lr_scheduler: cosine
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max_steps: 1
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micro_batch_size: 2
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mlflow_experiment_name: /tmp/75e2dfb45725a08d_train_data.json
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model_type: AutoModelForCausalLM
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num_epochs: 1
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wandb_project: Gradients-On-Demand
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wandb_run: your_name
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wandb_runid: decda85a-cc80-403f-8f61-2d4405578f06
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warmup_steps: 1
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weight_decay: 0.0
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xformers_attention: null
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# decda85a-cc80-403f-8f61-2d4405578f06
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This model is a fine-tuned version of [unsloth/Qwen2.5-Math-1.5B](https://huggingface.co/unsloth/Qwen2.5-Math-1.5B) on the None dataset.
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## Model description
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The following hyperparameters were used during training:
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- learning_rate: 0.0001
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- train_batch_size: 2
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- eval_batch_size: 2
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 8
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- optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_steps: 2
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- training_steps: 1
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:------:|:----:|:---------------:|
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| No log | 0.0047 | 1 | nan |
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### Framework versions
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adapter_model.bin
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size 37070634
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