End of training
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- adapter_model.bin +2 -2
README.md
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---
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license:
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library_name: peft
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tags:
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- axolotl
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- generated_from_trainer
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base_model:
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model-index:
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- name:
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results: []
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---
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@@ -19,19 +19,19 @@ should probably proofread and complete it, then remove this comment. -->
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axolotl version: `0.4.1`
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```yaml
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adapter: lora
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base_model:
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bf16: auto
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datasets:
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- data_files:
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-
-
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ds_type: json
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format: custom
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path:
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type:
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field: null
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field_input: null
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-
field_instruction:
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field_output:
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field_system: null
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format: null
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no_input_format: null
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gradient_accumulation_steps: 4
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gradient_checkpointing: true
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group_by_length: false
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hub_model_id: FatCat87/
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learning_rate: 0.0002
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load_in_4bit: false
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load_in_8bit: true
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resume_from_checkpoint: null
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sample_packing: true
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saves_per_epoch: 1
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-
seed:
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sequence_len: 4096
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special_tokens:
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strict: false
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tf32: false
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tokenizer_type: AutoTokenizer
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wandb_entity: fatcat87-taopanda
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wandb_log_model: null
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wandb_mode: online
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wandb_name:
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wandb_project: subnet56
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wandb_runid:
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wandb_watch: null
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warmup_ratio: 0.05
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weight_decay: 0.0
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</details><br>
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-
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/fatcat87-taopanda/subnet56/runs/
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#
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This model is a fine-tuned version of [
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It achieves the following results on the evaluation set:
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- Loss:
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## Model description
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- learning_rate: 0.0002
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- train_batch_size: 2
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- eval_batch_size: 2
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-
- seed:
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- distributed_type: multi-GPU
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- num_devices: 2
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- gradient_accumulation_steps: 4
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- total_eval_batch_size: 4
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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_steps: 2
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- num_epochs: 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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-
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-
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-
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-
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### Framework versions
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---
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license: apache-2.0
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library_name: peft
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tags:
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- axolotl
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- generated_from_trainer
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base_model: EleutherAI/pythia-70m-deduped
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model-index:
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- name: 6d89a915-cad3-42ab-8d1a-5e9e9e98151c
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results: []
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---
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axolotl version: `0.4.1`
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```yaml
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adapter: lora
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base_model: EleutherAI/pythia-70m-deduped
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bf16: auto
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datasets:
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- data_files:
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- c0e356afd17a58f1_train_data.json
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ds_type: json
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format: custom
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path: c0e356afd17a58f1_train_data.json
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type:
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field: null
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field_input: null
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field_instruction: ruby_text
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field_output: text
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field_system: null
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format: null
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no_input_format: null
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gradient_accumulation_steps: 4
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gradient_checkpointing: true
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group_by_length: false
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hub_model_id: FatCat87/6d89a915-cad3-42ab-8d1a-5e9e9e98151c
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learning_rate: 0.0002
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load_in_4bit: false
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load_in_8bit: true
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resume_from_checkpoint: null
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sample_packing: true
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saves_per_epoch: 1
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seed: 26260
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sequence_len: 4096
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special_tokens:
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pad_token: <|endoftext|>
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strict: false
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tf32: false
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tokenizer_type: AutoTokenizer
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wandb_entity: fatcat87-taopanda
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wandb_log_model: null
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wandb_mode: online
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wandb_name: 6d89a915-cad3-42ab-8d1a-5e9e9e98151c
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wandb_project: subnet56
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wandb_runid: 6d89a915-cad3-42ab-8d1a-5e9e9e98151c
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wandb_watch: null
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warmup_ratio: 0.05
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weight_decay: 0.0
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</details><br>
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/fatcat87-taopanda/subnet56/runs/51bg82x5)
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# 6d89a915-cad3-42ab-8d1a-5e9e9e98151c
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This model is a fine-tuned version of [EleutherAI/pythia-70m-deduped](https://huggingface.co/EleutherAI/pythia-70m-deduped) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 32.2953
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## Model description
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- learning_rate: 0.0002
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- train_batch_size: 2
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- eval_batch_size: 2
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- seed: 26260
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- distributed_type: multi-GPU
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- num_devices: 2
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- gradient_accumulation_steps: 4
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- total_eval_batch_size: 4
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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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- num_epochs: 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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| 48.9386 | 0.0635 | 1 | 45.6835 |
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| 47.7809 | 0.2540 | 4 | 44.7200 |
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| 34.2772 | 0.5079 | 8 | 38.5010 |
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| 30.6758 | 0.7619 | 12 | 32.2953 |
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### Framework versions
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adapter_model.bin
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