Improve language tag

README.md

@@ -1,72 +1,86 @@
----
-library_name: transformers
-license: other
-base_model: Qwen/Qwen2.5-7B
-tags:
-- llama-factory
-- full
-- generated_from_trainer
-model-index:
-- name: qwen
-  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. -->
-
-# qwen
-
-This model is a fine-tuned version of [/inspire/hdd/ws-8207e9e2-e733-4eec-a475-cfa1c36480ba/embodied-multimodality/public/yli/workspace/Model/Qwen/Qwen2.5-7B](https://huggingface.co//inspire/hdd/ws-8207e9e2-e733-4eec-a475-cfa1c36480ba/embodied-multimodality/public/yli/workspace/Model/Qwen/Qwen2.5-7B) on the 2wikimultihopqa_train, the hotpotqa_train and the musique_train datasets.
-It achieves the following results on the evaluation set:
-- Loss: 0.1587
-
-## 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: 7e-06
-- train_batch_size: 4
-- eval_batch_size: 1
-- seed: 42
-- distributed_type: multi-GPU
-- num_devices: 8
-- gradient_accumulation_steps: 4
-- total_train_batch_size: 128
-- total_eval_batch_size: 8
-- 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_ratio: 0.1
-- num_epochs: 3.0
-
-### Training results
-
-| Training Loss | Epoch  | Step | Validation Loss |
-|:-------------:|:------:|:----:|:---------------:|
-| 0.1713        | 0.3842 | 500  | 0.1614          |
-| 0.1549        | 0.7685 | 1000 | 0.1432          |
-| 0.0948        | 1.1527 | 1500 | 0.1415          |
-| 0.0846        | 1.5370 | 2000 | 0.1369          |
-| 0.0841        | 1.9212 | 2500 | 0.1317          |
-| 0.0375        | 2.3055 | 3000 | 0.1596          |
-| 0.0366        | 2.6897 | 3500 | 0.1586          |
-
-
-### Framework versions
-
-- Transformers 4.46.1
-- Pytorch 2.4.0
-- Datasets 3.1.0
-- Tokenizers 0.20.3
+---
+library_name: transformers
+license: other
+base_model: Qwen/Qwen2.5-7B
+tags:
+- llama-factory
+- full
+- generated_from_trainer
+language:
+- zho
+- eng
+- fra
+- spa
+- por
+- deu
+- ita
+- rus
+- jpn
+- kor
+- vie
+- tha
+- ara
+model-index:
+- name: qwen
+  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. -->
+
+# qwen
+
+This model is a fine-tuned version of [/inspire/hdd/ws-8207e9e2-e733-4eec-a475-cfa1c36480ba/embodied-multimodality/public/yli/workspace/Model/Qwen/Qwen2.5-7B](https://huggingface.co//inspire/hdd/ws-8207e9e2-e733-4eec-a475-cfa1c36480ba/embodied-multimodality/public/yli/workspace/Model/Qwen/Qwen2.5-7B) on the 2wikimultihopqa_train, the hotpotqa_train and the musique_train datasets.
+It achieves the following results on the evaluation set:
+- Loss: 0.1587
+
+## 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: 7e-06
+- train_batch_size: 4
+- eval_batch_size: 1
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 8
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 128
+- total_eval_batch_size: 8
+- 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_ratio: 0.1
+- num_epochs: 3.0
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss |
+|:-------------:|:------:|:----:|:---------------:|
+| 0.1713        | 0.3842 | 500  | 0.1614          |
+| 0.1549        | 0.7685 | 1000 | 0.1432          |
+| 0.0948        | 1.1527 | 1500 | 0.1415          |
+| 0.0846        | 1.5370 | 2000 | 0.1369          |
+| 0.0841        | 1.9212 | 2500 | 0.1317          |
+| 0.0375        | 2.3055 | 3000 | 0.1596          |
+| 0.0366        | 2.6897 | 3500 | 0.1586          |
+
+
+### Framework versions
+
+- Transformers 4.46.1
+- Pytorch 2.4.0
+- Datasets 3.1.0
+- Tokenizers 0.20.3