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--- |
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base_model: TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T |
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library_name: peft |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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- Axolotl |
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- fine tuned |
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model-index: |
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- name: outputs/lora-out |
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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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[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl) |
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<details><summary>See axolotl config</summary> |
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axolotl version: `0.4.1` |
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```yaml |
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base_model: TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T |
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model_type: LlamaForCausalLM |
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tokenizer_type: LlamaTokenizer |
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load_in_8bit: true |
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load_in_4bit: false |
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strict: false |
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datasets: |
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- path: mhenrichsen/alpaca_2k_test |
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type: alpaca |
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dataset_prepared_path: |
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val_set_size: 0.05 |
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output_dir: ./outputs/lora-out |
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sequence_len: 4096 |
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sample_packing: true |
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eval_sample_packing: false |
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pad_to_sequence_len: true |
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adapter: lora |
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lora_model_dir: |
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lora_r: 32 |
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lora_alpha: 16 |
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lora_dropout: 0.05 |
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lora_target_linear: true |
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lora_fan_in_fan_out: |
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wandb_project: |
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wandb_entity: |
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wandb_watch: |
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wandb_name: |
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wandb_log_model: |
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gradient_accumulation_steps: 4 |
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micro_batch_size: 2 |
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num_epochs: 4 |
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optimizer: adamw_bnb_8bit |
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lr_scheduler: cosine |
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learning_rate: 0.0002 |
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train_on_inputs: false |
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group_by_length: false |
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bf16: auto |
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fp16: |
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tf32: false |
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gradient_checkpointing: true |
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early_stopping_patience: |
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resume_from_checkpoint: |
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local_rank: |
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logging_steps: 1 |
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xformers_attention: |
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flash_attention: true |
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warmup_steps: 10 |
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evals_per_epoch: 4 |
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saves_per_epoch: 1 |
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debug: |
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deepspeed: |
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weight_decay: 0.0 |
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fsdp: |
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fsdp_config: |
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special_tokens: |
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``` |
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</details><br> |
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# outputs/lora-out |
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This model is a fine-tuned version of [TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T](https://huggingface.co/TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.2122 |
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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: 0.0002 |
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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: 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: 10 |
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- num_epochs: 4 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 1.4615 | 0.08 | 1 | 1.4899 | |
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| 1.3849 | 0.24 | 3 | 1.4852 | |
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| 1.3665 | 0.48 | 6 | 1.4411 | |
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| 1.2689 | 0.72 | 9 | 1.3381 | |
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| 1.2258 | 0.96 | 12 | 1.2960 | |
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| 1.2518 | 1.16 | 15 | 1.2797 | |
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| 1.2263 | 1.4 | 18 | 1.2534 | |
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| 1.1343 | 1.6400 | 21 | 1.2354 | |
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| 1.2699 | 1.88 | 24 | 1.2255 | |
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| 1.1493 | 2.08 | 27 | 1.2228 | |
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| 1.153 | 2.32 | 30 | 1.2188 | |
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| 1.1947 | 2.56 | 33 | 1.2183 | |
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| 1.1125 | 2.8 | 36 | 1.2157 | |
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| 1.1512 | 3.04 | 39 | 1.2123 | |
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| 1.1883 | 3.24 | 42 | 1.2100 | |
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| 1.1012 | 3.48 | 45 | 1.2119 | |
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| 1.1891 | 3.7200 | 48 | 1.2122 | |
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### Framework versions |
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- PEFT 0.11.1 |
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- Transformers 4.41.1 |
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- Pytorch 2.1.2+cu118 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
