Improve language tag

Hi! As the model is multilingual, this is a PR to add other languages than English to the language tag to improve the referencing. Note that 29 languages are announced in the README, but only 13 are explicitly listed. I was therefore only able to add these 13 languages.

README.md

@@ -1,138 +1,152 @@
----
-library_name: peft
-license: apache-2.0
-base_model: Qwen/Qwen2.5-7B-Instruct
-tags:
-- generated_from_trainer
-datasets:
-- ugaoo/pubmedqa_train
-model-index:
-- name: out/Qwen_Qwen2.5_7B_Instruct_ugaoo_pubmedqa_train
-  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: Qwen/Qwen2.5-7B-Instruct
-model_type: AutoModelForCausalLM
-tokenizer_type: AutoTokenizer
-trust_remote_code: true
-
-load_in_8bit: false
-load_in_4bit: true
-strict: false
-
-datasets:
-  - path: ugaoo/pubmedqa_train
-    type: alpaca
-val_set_size: 0
-output_dir: ./out/Qwen_Qwen2.5_7B_Instruct_ugaoo_pubmedqa_train
-
-sequence_len: 4000
-sample_packing: true
-pad_to_sequence_len: true
-
-adapter: qlora
-lora_r: 256
-lora_alpha: 512
-lora_dropout: 0.05
-lora_target_linear: true
-lora_target_modules:
-  - q_proj
-  - k_proj
-  - v_proj
-  - o_proj
-  - up_proj
-  - down_proj
-  - gate_proj
- 
-wandb_project: testsearch
-wandb_entity:
-wandb_watch: 
-wandb_name: Qwen_Qwen2.5_7B_Instruct_ugaoo_pubmedqa_train
-wandb_log_model:
-
-gradient_accumulation_steps: 3
-micro_batch_size: 4
-num_epochs: 6
-optimizer: adamw_torch
-lr_scheduler: cosine
-learning_rate: 5e-6
-
-train_on_inputs: false
-group_by_length: false
-bf16: auto
-fp16: false
-tf32: false
-
-gradient_checkpointing: true
-early_stopping_patience:
-resume_from_checkpoint:
-logging_steps: 1
-xformers_attention:
-flash_attention: true
-
-warmup_steps: 100
-evals_per_epoch: 6
-eval_table_size:
-saves_per_epoch: 1
-debug:
-deepspeed:
-weight_decay: 0.0
-fsdp:
-fsdp_config:
-save_total_limit: 6
-```
-
-</details><br>
-
-# out/Qwen_Qwen2.5_7B_Instruct_ugaoo_pubmedqa_train
-
-This model is a fine-tuned version of [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct) on the ugaoo/pubmedqa_train dataset.
-
-## 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: 5e-06
-- train_batch_size: 4
-- eval_batch_size: 4
-- seed: 42
-- distributed_type: multi-GPU
-- gradient_accumulation_steps: 3
-- total_train_batch_size: 12
-- optimizer: Use OptimizerNames.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: 100
-- num_epochs: 6.0
-
-### Training results
-
-
-
-### Framework versions
-
-- PEFT 0.14.0
-- Transformers 4.49.0
-- Pytorch 2.5.1+cu124
-- Datasets 3.2.0
+---
+library_name: peft
+license: apache-2.0
+base_model: Qwen/Qwen2.5-7B-Instruct
+tags:
+- generated_from_trainer
+datasets:
+- ugaoo/pubmedqa_train
+language:
+- zho
+- eng
+- fra
+- spa
+- por
+- deu
+- ita
+- rus
+- jpn
+- kor
+- vie
+- tha
+- ara
+model-index:
+- name: out/Qwen_Qwen2.5_7B_Instruct_ugaoo_pubmedqa_train
+  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: Qwen/Qwen2.5-7B-Instruct
+model_type: AutoModelForCausalLM
+tokenizer_type: AutoTokenizer
+trust_remote_code: true
+
+load_in_8bit: false
+load_in_4bit: true
+strict: false
+
+datasets:
+  - path: ugaoo/pubmedqa_train
+    type: alpaca
+val_set_size: 0
+output_dir: ./out/Qwen_Qwen2.5_7B_Instruct_ugaoo_pubmedqa_train
+
+sequence_len: 4000
+sample_packing: true
+pad_to_sequence_len: true
+
+adapter: qlora
+lora_r: 256
+lora_alpha: 512
+lora_dropout: 0.05
+lora_target_linear: true
+lora_target_modules:
+  - q_proj
+  - k_proj
+  - v_proj
+  - o_proj
+  - up_proj
+  - down_proj
+  - gate_proj
+ 
+wandb_project: testsearch
+wandb_entity:
+wandb_watch: 
+wandb_name: Qwen_Qwen2.5_7B_Instruct_ugaoo_pubmedqa_train
+wandb_log_model:
+
+gradient_accumulation_steps: 3
+micro_batch_size: 4
+num_epochs: 6
+optimizer: adamw_torch
+lr_scheduler: cosine
+learning_rate: 5e-6
+
+train_on_inputs: false
+group_by_length: false
+bf16: auto
+fp16: false
+tf32: false
+
+gradient_checkpointing: true
+early_stopping_patience:
+resume_from_checkpoint:
+logging_steps: 1
+xformers_attention:
+flash_attention: true
+
+warmup_steps: 100
+evals_per_epoch: 6
+eval_table_size:
+saves_per_epoch: 1
+debug:
+deepspeed:
+weight_decay: 0.0
+fsdp:
+fsdp_config:
+save_total_limit: 6
+```
+
+</details><br>
+
+# out/Qwen_Qwen2.5_7B_Instruct_ugaoo_pubmedqa_train
+
+This model is a fine-tuned version of [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct) on the ugaoo/pubmedqa_train dataset.
+
+## 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: 5e-06
+- train_batch_size: 4
+- eval_batch_size: 4
+- seed: 42
+- distributed_type: multi-GPU
+- gradient_accumulation_steps: 3
+- total_train_batch_size: 12
+- optimizer: Use OptimizerNames.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: 100
+- num_epochs: 6.0
+
+### Training results
+
+
+
+### Framework versions
+
+- PEFT 0.14.0
+- Transformers 4.49.0
+- Pytorch 2.5.1+cu124
+- Datasets 3.2.0
 - Tokenizers 0.21.0