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 +159 -145

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@@ -1,146 +1,160 @@
----
-library_name: peft
-license: other
-base_model: Qwen/Qwen2.5-72B
-tags:
-- axolotl
-- generated_from_trainer
-datasets:
-- sumuks/openreview_wintermute_0.2_training_data
-model-index:
-- name: purple-wintermute-0.2-72b
-  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/Qwen2.5-72B
-hub_model_id: sumuks/purple-wintermute-0.2-72b
-trust_remote_code: true
-load_in_8bit: false
-load_in_4bit: false
-strict: false
-bf16: true
-hf_use_auth_token: true
-plugins:
-  - axolotl.integrations.liger.LigerPlugin
-liger_rope: true
-liger_rms_norm: true
-liger_glu_activation: true
-liger_layer_norm: true
-liger_fused_linear_cross_entropy: true
-save_safetensors:
-datasets:
-  - path: sumuks/openreview_wintermute_0.2_training_data
-    type: completion
-    field: text
-dataset_prepared_path: .axolotl_cache_data/wintermute_0.2
-shuffle_merged_datasets: true
-# dataset_exact_deduplication: true
-val_set_size: 0.005
-output_dir: ./../../outputs/purple-wintermute-0.2-72b
-push_dataset_to_hub: sumuks/purple_wintermute_0.2_training_data_in_progress
-sequence_length: 2048
-sample_packing: true
-pad_to_sequence_len: true
-adapter: lora
-lora_r: 256
-lora_alpha: 32
-lora_dropout: 0.05
-peft_use_rslora: true
-lora_target_linear: true
-gradient_accumulation_steps: 4
-micro_batch_size: 8
-eval_batch_size: 1
-num_epochs: 3
-learning_rate: 5e-5
-warmup_ratio: 0.05
-evals_per_epoch: 3
-saves_per_epoch: 5
-gradient_checkpointing: true
-lr_scheduler: cosine
-optimizer: paged_adamw_8bit
-profiler_steps: 100
-save_safetensors: true
-train_on_inputs: true
-wandb_project: wintermute
-wandb_name: purple-wintermute-0.2-72b
-deepspeed: deepspeed_configs/zero3_bf16.json
-```
-</details><br>
-# purple-wintermute-0.2-72b
-This model is a fine-tuned version of [Qwen/Qwen2.5-72B](https://huggingface.co/Qwen/Qwen2.5-72B) on the sumuks/openreview_wintermute_0.2_training_data dataset.
-It achieves the following results on the evaluation set:
-- Loss: 1.3017
-## 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-05
-- train_batch_size: 8
-- eval_batch_size: 1
-- seed: 42
-- distributed_type: multi-GPU
-- num_devices: 8
-- gradient_accumulation_steps: 4
-- total_train_batch_size: 256
-- total_eval_batch_size: 8
-- optimizer: Use paged_adamw_8bit 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: 388
-- num_epochs: 3
-### Training results
-| Training Loss | Epoch  | Step | Validation Loss |
-|:-------------:|:------:|:----:|:---------------:|
-| No log        | 0.0004 | 1    | 2.5112          |
-| 1.3654        | 0.3333 | 864  | 1.6504          |
-| 0.9929        | 0.6665 | 1728 | 1.4144          |
-| 0.9039        | 0.9998 | 2592 | 1.3083          |
-| 0.8161        | 1.3333 | 3456 | 1.2935          |
-| 0.7815        | 1.6665 | 4320 | 1.2816          |
-| 0.7658        | 1.9998 | 5184 | 1.2775          |
-| 0.7004        | 2.3333 | 6048 | 1.2995          |
-| 0.6694        | 2.6665 | 6912 | 1.3013          |
-| 0.6798        | 2.9998 | 7776 | 1.3017          |
-### Framework versions
-- PEFT 0.14.0
-- Transformers 4.47.1
-- Pytorch 2.5.1
-- Datasets 3.2.0
 - Tokenizers 0.21.0

+---
+library_name: peft
+license: other
+base_model: Qwen/Qwen2.5-72B
+tags:
+- axolotl
+- generated_from_trainer
+datasets:
+- sumuks/openreview_wintermute_0.2_training_data
+language:
+- zho
+- eng
+- fra
+- spa
+- por
+- deu
+- ita
+- rus
+- jpn
+- kor
+- vie
+- tha
+- ara
+model-index:
+- name: purple-wintermute-0.2-72b
+  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/Qwen2.5-72B
+hub_model_id: sumuks/purple-wintermute-0.2-72b
+trust_remote_code: true
+load_in_8bit: false
+load_in_4bit: false
+strict: false
+bf16: true
+hf_use_auth_token: true
+plugins:
+  - axolotl.integrations.liger.LigerPlugin
+liger_rope: true
+liger_rms_norm: true
+liger_glu_activation: true
+liger_layer_norm: true
+liger_fused_linear_cross_entropy: true
+save_safetensors:
+datasets:
+  - path: sumuks/openreview_wintermute_0.2_training_data
+    type: completion
+    field: text
+dataset_prepared_path: .axolotl_cache_data/wintermute_0.2
+shuffle_merged_datasets: true
+# dataset_exact_deduplication: true
+val_set_size: 0.005
+output_dir: ./../../outputs/purple-wintermute-0.2-72b
+push_dataset_to_hub: sumuks/purple_wintermute_0.2_training_data_in_progress
+sequence_length: 2048
+sample_packing: true
+pad_to_sequence_len: true
+adapter: lora
+lora_r: 256
+lora_alpha: 32
+lora_dropout: 0.05
+peft_use_rslora: true
+lora_target_linear: true
+gradient_accumulation_steps: 4
+micro_batch_size: 8
+eval_batch_size: 1
+num_epochs: 3
+learning_rate: 5e-5
+warmup_ratio: 0.05
+evals_per_epoch: 3
+saves_per_epoch: 5
+gradient_checkpointing: true
+lr_scheduler: cosine
+optimizer: paged_adamw_8bit
+profiler_steps: 100
+save_safetensors: true
+train_on_inputs: true
+wandb_project: wintermute
+wandb_name: purple-wintermute-0.2-72b
+deepspeed: deepspeed_configs/zero3_bf16.json
+```
+</details><br>
+# purple-wintermute-0.2-72b
+This model is a fine-tuned version of [Qwen/Qwen2.5-72B](https://huggingface.co/Qwen/Qwen2.5-72B) on the sumuks/openreview_wintermute_0.2_training_data dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.3017
+## 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-05
+- train_batch_size: 8
+- eval_batch_size: 1
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 8
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 256
+- total_eval_batch_size: 8
+- optimizer: Use paged_adamw_8bit 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: 388
+- num_epochs: 3
+### Training results
+| Training Loss | Epoch  | Step | Validation Loss |
+|:-------------:|:------:|:----:|:---------------:|
+| No log        | 0.0004 | 1    | 2.5112          |
+| 1.3654        | 0.3333 | 864  | 1.6504          |
+| 0.9929        | 0.6665 | 1728 | 1.4144          |
+| 0.9039        | 0.9998 | 2592 | 1.3083          |
+| 0.8161        | 1.3333 | 3456 | 1.2935          |
+| 0.7815        | 1.6665 | 4320 | 1.2816          |
+| 0.7658        | 1.9998 | 5184 | 1.2775          |
+| 0.7004        | 2.3333 | 6048 | 1.2995          |
+| 0.6694        | 2.6665 | 6912 | 1.3013          |
+| 0.6798        | 2.9998 | 7776 | 1.3017          |
+### Framework versions
+- PEFT 0.14.0
+- Transformers 4.47.1
+- Pytorch 2.5.1
+- Datasets 3.2.0
 - Tokenizers 0.21.0