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.

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README.md +165 -151

README.md CHANGED Viewed

@@ -1,152 +1,166 @@
----
-library_name: peft
-license: apache-2.0
-base_model: Qwen/Qwen2.5-7B-Instruct
-tags:
-- generated_from_trainer
-datasets:
-- aaditya/mimicraw_clinicaltrial_train
-model-index:
-- name: out
-  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
-model_type: AutoModelForCausalLM
-tokenizer_type: AutoTokenizer
-trust_remote_code: true
-load_in_8bit: false
-load_in_4bit: true
-strict: false
-datasets:
-  - path: aaditya/mimicraw_clinicaltrial_train
-    type: alpaca
-val_set_size: 0.05
-output_dir: ./out
-sequence_len: 4096
-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
-  - gate_proj
-  - down_proj
-  - up_proj
-wandb_project: qwen_mimicrawclinicaltrail
-wandb_entity:
-wandb_watch:
-wandb_name:
-wandb_log_model:
-gradient_accumulation_steps: 4
-micro_batch_size: 6
-num_epochs: 3
-optimizer: adamw_torch
-lr_scheduler: cosine
-learning_rate: 2e-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: 3
-eval_table_size:
-saves_per_epoch: 1
-debug:
-deepspeed:
-weight_decay: 0.0
-fsdp:
-fsdp_config:
-save_total_limit: 4
-```
-</details><br>
-# out
-This model is a fine-tuned version of [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct) on the aaditya/mimicraw_clinicaltrial_train dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.6060
-## 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: 2e-06
-- train_batch_size: 6
-- eval_batch_size: 6
-- seed: 42
-- distributed_type: multi-GPU
-- gradient_accumulation_steps: 4
-- total_train_batch_size: 24
-- 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: 3
-### Training results
-| Training Loss | Epoch  | Step | Validation Loss |
-|:-------------:|:------:|:----:|:---------------:|
-| 0.8273        | 0.0008 | 1    | 0.8615          |
-| 0.6312        | 0.3335 | 400  | 0.6677          |
-| 0.6221        | 0.6671 | 800  | 0.6416          |
-| 0.1335        | 1.0    | 1200 | 0.6267          |
-| 0.6062        | 1.3327 | 1600 | 0.6176          |
-| 0.5861        | 1.6662 | 2000 | 0.6119          |
-| 0.6194        | 1.9998 | 2400 | 0.6084          |
-| 0.5953        | 2.3319 | 2800 | 0.6068          |
-| 0.6394        | 2.6654 | 3200 | 0.6060          |
-### Framework versions
-- PEFT 0.14.0
-- Transformers 4.48.1
-- Pytorch 2.5.1+cu124
-- Datasets 3.2.0
 - Tokenizers 0.21.0

+---
+library_name: peft
+license: apache-2.0
+base_model: Qwen/Qwen2.5-7B-Instruct
+tags:
+- generated_from_trainer
+datasets:
+- aaditya/mimicraw_clinicaltrial_train
+language:
+- zho
+- eng
+- fra
+- spa
+- por
+- deu
+- ita
+- rus
+- jpn
+- kor
+- vie
+- tha
+- ara
+model-index:
+- name: out
+  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
+model_type: AutoModelForCausalLM
+tokenizer_type: AutoTokenizer
+trust_remote_code: true
+load_in_8bit: false
+load_in_4bit: true
+strict: false
+datasets:
+  - path: aaditya/mimicraw_clinicaltrial_train
+    type: alpaca
+val_set_size: 0.05
+output_dir: ./out
+sequence_len: 4096
+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
+  - gate_proj
+  - down_proj
+  - up_proj
+wandb_project: qwen_mimicrawclinicaltrail
+wandb_entity:
+wandb_watch:
+wandb_name:
+wandb_log_model:
+gradient_accumulation_steps: 4
+micro_batch_size: 6
+num_epochs: 3
+optimizer: adamw_torch
+lr_scheduler: cosine
+learning_rate: 2e-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: 3
+eval_table_size:
+saves_per_epoch: 1
+debug:
+deepspeed:
+weight_decay: 0.0
+fsdp:
+fsdp_config:
+save_total_limit: 4
+```
+</details><br>
+# out
+This model is a fine-tuned version of [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct) on the aaditya/mimicraw_clinicaltrial_train dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6060
+## 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: 2e-06
+- train_batch_size: 6
+- eval_batch_size: 6
+- seed: 42
+- distributed_type: multi-GPU
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 24
+- 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: 3
+### Training results
+| Training Loss | Epoch  | Step | Validation Loss |
+|:-------------:|:------:|:----:|:---------------:|
+| 0.8273        | 0.0008 | 1    | 0.8615          |
+| 0.6312        | 0.3335 | 400  | 0.6677          |
+| 0.6221        | 0.6671 | 800  | 0.6416          |
+| 0.1335        | 1.0    | 1200 | 0.6267          |
+| 0.6062        | 1.3327 | 1600 | 0.6176          |
+| 0.5861        | 1.6662 | 2000 | 0.6119          |
+| 0.6194        | 1.9998 | 2400 | 0.6084          |
+| 0.5953        | 2.3319 | 2800 | 0.6068          |
+| 0.6394        | 2.6654 | 3200 | 0.6060          |
+### Framework versions
+- PEFT 0.14.0
+- Transformers 4.48.1
+- Pytorch 2.5.1+cu124
+- Datasets 3.2.0
 - Tokenizers 0.21.0