seacorn
/

llama3.1-8b-reasoning-summarizer

@@ -1,199 +1,158 @@
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-library_name: transformers
-tags: []
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 ---
+library_name: peft
+license: llama3.1
+base_model: meta-llama/Llama-3.1-8B-Instruct
+tags:
+- axolotl
+- generated_from_trainer
+datasets:
+- seacorn/news-summarizer-reasoner
+model-index:
+- name: llama3.1-8b-reasoning-summarizer
+  results: []
 ---
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
+<details><summary>See axolotl config</summary>
+axolotl version: `0.8.0.dev0`
+```yaml
+base_model: meta-llama/Llama-3.1-8B-Instruct
+# optionally might have model_type or tokenizer_type
+model_type: LlamaForCausalLM
+tokenizer_type: AutoTokenizer
+# Automatically upload checkpoint and final model to HF
+hub_model_id: seacorn/llama3.1-8b-reasoning-summarizer
+load_in_8bit: true
+load_in_4bit: false
+strict: false
+seed: 42
+datasets:
+  - path: output.jsonl
+    type: chat_template
+dataset_prepared_path:
+val_set_size: 0.05
+output_dir: ./lora-out
+sequence_len: 8192
+sample_packing: true
+eval_sample_packing: false
+pad_to_sequence_len: true
+adapter: lora
+lora_model_dir:
+lora_r: 16
+lora_alpha: 32
+lora_dropout: 0.05
+lora_target_linear: true
+lora_fan_in_fan_out:
+lora_modules_to_save:
+  - embed_tokens
+  - lm_head
+wandb_project: huggingface
+wandb_entity:
+wandb_watch:
+wandb_name: llama3.1-8b-reasoning-summarizer
+wandb_log_model:
+gradient_accumulation_steps: 4
+micro_batch_size: 2
+num_epochs: 2
+optimizer: adamw_bnb_8bit
+lr_scheduler: cosine
+learning_rate: 0.0002
+train_on_inputs: false
+group_by_length: false
+bf16: auto
+fp16:
+tf32: false
+gradient_checkpointing: true
+early_stopping_patience:
+resume_from_checkpoint:
+local_rank:
+logging_steps: 1
+xformers_attention:
+flash_attention: true
+s2_attention:
+warmup_ratio: 0.05
+evals_per_epoch: 4
+eval_table_size:
+eval_max_new_tokens: 128
+saves_per_epoch: 5
+debug:
+deepspeed:
+weight_decay: 0.0
+fsdp:
+fsdp_config:
+special_tokens:
+   pad_token: <|end_of_text|>
+```
+</details><br>
+# llama3.1-8b-reasoning-summarizer
+This model is a fine-tuned version of [meta-llama/Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct) on the [seacorn/news-summarizer-reasoner](https://huggingface.co/datasets/seacorn/news-summarizer-reasoner) dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.1173
+## Model description
+More information needed
+## Intended uses & limitations
+More information needed
+## Training and evaluation data
+More information needed
+## Training procedure
+### Training hyperparameters
+The following hyperparameters were used during training:
+- learning_rate: 0.0002
+- train_batch_size: 2
+- eval_batch_size: 2
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 8
+- optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 56
+- num_epochs: 2.0
+### Training results
+| Training Loss | Epoch  | Step | Validation Loss |
+|:-------------:|:------:|:----:|:---------------:|
+| 2.0396        | 0.0018 | 1    | 1.7982          |
+| 1.3908        | 0.2506 | 141  | 1.2241          |
+| 1.8534        | 0.5011 | 282  | 1.1842          |
+| 1.5745        | 0.7517 | 423  | 1.1560          |
+| 0.9261        | 1.0018 | 564  | 1.1288          |
+| 1.2359        | 1.2523 | 705  | 1.1344          |
+| 1.1835        | 1.5029 | 846  | 1.1223          |
+| 0.9898        | 1.7534 | 987  | 1.1173          |
+### Framework versions
+- PEFT 0.15.0
+- Transformers 4.50.0
+- Pytorch 2.5.1+cu124
+- Datasets 3.4.1
+- Tokenizers 0.21.1