End of training

README.md

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+---
+library_name: peft
+license: apache-2.0
+base_model: Qwen/Qwen2.5-7B-Instruct
+tags:
+- axolotl
+- generated_from_trainer
+datasets:
+- medalpaca/medical_meadow_medqa
+model-index:
+- name: lora-qwen-25-7b-instruct
+  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: `0.6.0`
+```yaml
+base_model: Qwen/Qwen2.5-7B-Instruct
+trust_remote_code: true
+model_type: AutoModelForCausalLM
+tokenizer_type: AutoTokenizer
+
+load_in_8bit: 
+load_in_4bit:
+strict: false
+
+datasets:
+  - path: medalpaca/medical_meadow_medqa
+    type: alpaca
+dataset_prepared_path:
+val_set_size: 0.1
+output_dir: ./lora-qwen25
+
+sequence_len: 8192
+sample_packing: true
+eval_sample_packing: true
+pad_to_sequence_len: true
+
+
+adapter: lora
+lora_r: 256
+lora_alpha: 128
+lora_dropout: 0.05
+#lora_target_modules:
+#  - q_proj
+#  - v_proj
+#  - k_proj
+#  - o_proj
+#  - gate_proj
+#  - down_proj
+#  - up_proj
+lora_target_linear: true
+
+wandb_project: lora-qwen-25-7b-instruct
+wandb_entity: 
+wandb_watch:
+wandb_name: 
+wandb_log_model: 
+
+gradient_accumulation_steps: 1
+micro_batch_size: 1
+num_epochs: 3
+optimizer: adamw_torch
+lr_scheduler: cosine
+learning_rate: 0.00001
+
+train_on_inputs: false
+group_by_length: false
+bf16: true
+fp16: false
+tf32: false
+
+gradient_checkpointing: true
+  
+logging_steps: 1
+xformers_attention:
+flash_attention: true
+
+warmup_steps:
+eval_steps: 
+save_steps:
+
+evals_per_epoch: 16
+saves_per_epoch: 2
+
+debug:
+deepspeed: deepspeed_configs/zero2.json
+weight_decay:
+fsdp:
+fsdp_config:
+special_tokens:
+
+hub_model_id: neginashz/lora-qwen-25-7b-instruct
+hub_strategy: 
+early_stopping_patience:
+
+resume_from_checkpoint:
+auto_resume_from_checkpoints: true
+
+
+
+```
+
+</details><br>
+
+# lora-qwen-25-7b-instruct
+
+This model is a fine-tuned version of [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct) on the medalpaca/medical_meadow_medqa dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1181
+
+## 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: 1e-05
+- train_batch_size: 1
+- eval_batch_size: 1
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 4
+- total_train_batch_size: 4
+- total_eval_batch_size: 4
+- optimizer: Use adamw_torch 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: 7
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss |
+|:-------------:|:------:|:----:|:---------------:|
+| 2.774         | 0.0741 | 6    | 2.5571          |
+| 1.4649        | 0.1481 | 12   | 1.3144          |
+| 0.649         | 0.2222 | 18   | 0.4603          |
+| 0.1557        | 0.2963 | 24   | 0.1620          |
+| 0.1792        | 0.3704 | 30   | 0.1539          |
+| 0.1432        | 0.4444 | 36   | 0.1422          |
+| 0.1393        | 0.5185 | 42   | 0.1385          |
+| 0.1137        | 0.5926 | 48   | 0.1340          |
+| 0.1246        | 0.6667 | 54   | 0.1317          |
+| 0.1235        | 0.7407 | 60   | 0.1313          |
+| 0.123         | 0.8148 | 66   | 0.1293          |
+| 0.1413        | 0.8889 | 72   | 0.1277          |
+| 0.1338        | 0.9630 | 78   | 0.1268          |
+| 0.1093        | 1.0247 | 84   | 0.1263          |
+| 0.1442        | 1.0988 | 90   | 0.1265          |
+| 0.1127        | 1.1728 | 96   | 0.1244          |
+| 0.137         | 1.2469 | 102  | 0.1231          |
+| 0.1098        | 1.3210 | 108  | 0.1224          |
+| 0.1276        | 1.3951 | 114  | 0.1223          |
+| 0.102         | 1.4691 | 120  | 0.1215          |
+| 0.1208        | 1.5432 | 126  | 0.1217          |
+| 0.1143        | 1.6173 | 132  | 0.1211          |
+| 0.1315        | 1.6914 | 138  | 0.1204          |
+| 0.1166        | 1.7654 | 144  | 0.1200          |
+| 0.1055        | 1.8395 | 150  | 0.1200          |
+| 0.1235        | 1.9136 | 156  | 0.1194          |
+| 0.12          | 1.9877 | 162  | 0.1193          |
+| 0.0982        | 2.0494 | 168  | 0.1193          |
+| 0.1129        | 2.1235 | 174  | 0.1188          |
+| 0.1094        | 2.1975 | 180  | 0.1190          |
+| 0.1216        | 2.2716 | 186  | 0.1191          |
+| 0.1387        | 2.3457 | 192  | 0.1187          |
+| 0.1001        | 2.4198 | 198  | 0.1184          |
+| 0.1031        | 2.4938 | 204  | 0.1185          |
+| 0.0818        | 2.5679 | 210  | 0.1183          |
+| 0.126         | 2.6420 | 216  | 0.1185          |
+| 0.124         | 2.7160 | 222  | 0.1183          |
+| 0.1193        | 2.7901 | 228  | 0.1184          |
+| 0.1082        | 2.8642 | 234  | 0.1183          |
+| 0.1181        | 2.9383 | 240  | 0.1181          |
+
+
+### Framework versions
+
+- PEFT 0.14.0
+- Transformers 4.47.0
+- Pytorch 2.5.1+cu124
+- Datasets 3.1.0
+- Tokenizers 0.21.0

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