End of training
Browse files- README.md +164 -0
- adapter_model.bin +3 -0
README.md
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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: TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T
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model-index:
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- name: isafpr-tiny-llama-lora-templatefree
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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: false
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# I'm training on 4090 GPUs
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# so I'm using 4-bit precision to save on memory
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load_in_4bit: true
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strict: false
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data_seed: 42
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seed: 42
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datasets:
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- path: data/templatefree_isaf_press_releases_ft_train.jsonl
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type: input_output
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dataset_prepared_path:
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val_set_size: 0.1
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output_dir: ./outputs/tiny-llama/lora-out-templatefree
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hub_model_id: strickvl/isafpr-tiny-llama-lora-templatefree
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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: isaf_pr_ft
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wandb_entity: strickvl
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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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bos_token: "<s>"
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eos_token: "</s>"
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```
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</details><br>
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# isafpr-tiny-llama-lora-templatefree
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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: 0.0504
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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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- distributed_type: multi-GPU
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- num_devices: 2
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 16
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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: 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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| 1.8835 | 0.0274 | 1 | 1.8815 |
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| 1.2729 | 0.2466 | 9 | 1.1212 |
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| 0.2733 | 0.4932 | 18 | 0.2187 |
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| 0.1129 | 0.7397 | 27 | 0.0996 |
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| 0.0789 | 0.9863 | 36 | 0.0808 |
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| 0.0725 | 1.2123 | 45 | 0.0705 |
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| 0.0727 | 1.4589 | 54 | 0.0653 |
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| 0.0536 | 1.7055 | 63 | 0.0609 |
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| 0.0644 | 1.9521 | 72 | 0.0577 |
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| 0.0536 | 2.1781 | 81 | 0.0554 |
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| 0.0464 | 2.4247 | 90 | 0.0538 |
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| 0.054 | 2.6712 | 99 | 0.0522 |
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| 0.0512 | 2.9178 | 108 | 0.0511 |
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| 0.0463 | 3.1438 | 117 | 0.0508 |
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| 0.0523 | 3.3904 | 126 | 0.0505 |
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| 0.0473 | 3.6370 | 135 | 0.0504 |
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| 0.0459 | 3.8836 | 144 | 0.0504 |
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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 2.3.0+cu121
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- Datasets 2.19.1
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- Tokenizers 0.19.1
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adapter_model.bin
ADDED
@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:802280588472a42da60132455de9093bd308305b1bf217c410ad07028260d60f
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size 101036698
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