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

@@ -1,79 +1,93 @@
----
-library_name: peft
-license: apache-2.0
-base_model: Qwen/Qwen2.5-1.5B-Instruct
-tags:
-- generated_from_trainer
-model-index:
-- name: qwen_lora
-  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_lora
-
-This model is a fine-tuned version of [Qwen/Qwen2.5-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct) on an unknown dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.0622
-- Mse: 0.0622
-- Mae: 0.1968
-- R Squared: 0.3060
-
-## 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: 0.0001
-- train_batch_size: 128
-- eval_batch_size: 128
-- seed: 42
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-- lr_scheduler_type: cosine
-- lr_scheduler_warmup_ratio: 0.01
-- num_epochs: 5
-- mixed_precision_training: Native AMP
-
-### Training results
-
-| Training Loss | Epoch  | Step | Validation Loss | Mse    | Mae    | R Squared |
-|:-------------:|:------:|:----:|:---------------:|:------:|:------:|:---------:|
-| 0.0875        | 0.3115 | 100  | 0.0854          | 0.0854 | 0.2351 | 0.0471    |
-| 0.0786        | 0.6231 | 200  | 0.0741          | 0.0741 | 0.2186 | 0.1735    |
-| 0.0709        | 0.9346 | 300  | 0.0716          | 0.0716 | 0.2193 | 0.2018    |
-| 0.0675        | 1.2461 | 400  | 0.0735          | 0.0735 | 0.2106 | 0.1803    |
-| 0.0681        | 1.5576 | 500  | 0.0710          | 0.0710 | 0.2076 | 0.2081    |
-| 0.0627        | 1.8692 | 600  | 0.0675          | 0.0675 | 0.2059 | 0.2468    |
-| 0.0628        | 2.1807 | 700  | 0.0657          | 0.0657 | 0.2031 | 0.2677    |
-| 0.0591        | 2.4922 | 800  | 0.0646          | 0.0646 | 0.2033 | 0.2799    |
-| 0.06          | 2.8037 | 900  | 0.0660          | 0.0660 | 0.2007 | 0.2638    |
-| 0.0553        | 3.1153 | 1000 | 0.0633          | 0.0633 | 0.2012 | 0.2944    |
-| 0.0612        | 3.4268 | 1100 | 0.0654          | 0.0654 | 0.2078 | 0.2711    |
-| 0.0542        | 3.7383 | 1200 | 0.0627          | 0.0627 | 0.1987 | 0.3009    |
-| 0.0529        | 4.0498 | 1300 | 0.0623          | 0.0623 | 0.1970 | 0.3049    |
-| 0.0546        | 4.3614 | 1400 | 0.0624          | 0.0624 | 0.1962 | 0.3044    |
-| 0.0535        | 4.6729 | 1500 | 0.0623          | 0.0623 | 0.1972 | 0.3055    |
-| 0.0536        | 4.9844 | 1600 | 0.0622          | 0.0622 | 0.1968 | 0.3060    |
-
-
-### Framework versions
-
-- PEFT 0.13.2
-- Transformers 4.45.2
-- Pytorch 2.5.1+cu121
-- Datasets 3.1.0
+---
+library_name: peft
+license: apache-2.0
+base_model: Qwen/Qwen2.5-1.5B-Instruct
+tags:
+- generated_from_trainer
+language:
+- zho
+- eng
+- fra
+- spa
+- por
+- deu
+- ita
+- rus
+- jpn
+- kor
+- vie
+- tha
+- ara
+model-index:
+- name: qwen_lora
+  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_lora
+
+This model is a fine-tuned version of [Qwen/Qwen2.5-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0622
+- Mse: 0.0622
+- Mae: 0.1968
+- R Squared: 0.3060
+
+## 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: 0.0001
+- train_batch_size: 128
+- eval_batch_size: 128
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_ratio: 0.01
+- num_epochs: 5
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Mse    | Mae    | R Squared |
+|:-------------:|:------:|:----:|:---------------:|:------:|:------:|:---------:|
+| 0.0875        | 0.3115 | 100  | 0.0854          | 0.0854 | 0.2351 | 0.0471    |
+| 0.0786        | 0.6231 | 200  | 0.0741          | 0.0741 | 0.2186 | 0.1735    |
+| 0.0709        | 0.9346 | 300  | 0.0716          | 0.0716 | 0.2193 | 0.2018    |
+| 0.0675        | 1.2461 | 400  | 0.0735          | 0.0735 | 0.2106 | 0.1803    |
+| 0.0681        | 1.5576 | 500  | 0.0710          | 0.0710 | 0.2076 | 0.2081    |
+| 0.0627        | 1.8692 | 600  | 0.0675          | 0.0675 | 0.2059 | 0.2468    |
+| 0.0628        | 2.1807 | 700  | 0.0657          | 0.0657 | 0.2031 | 0.2677    |
+| 0.0591        | 2.4922 | 800  | 0.0646          | 0.0646 | 0.2033 | 0.2799    |
+| 0.06          | 2.8037 | 900  | 0.0660          | 0.0660 | 0.2007 | 0.2638    |
+| 0.0553        | 3.1153 | 1000 | 0.0633          | 0.0633 | 0.2012 | 0.2944    |
+| 0.0612        | 3.4268 | 1100 | 0.0654          | 0.0654 | 0.2078 | 0.2711    |
+| 0.0542        | 3.7383 | 1200 | 0.0627          | 0.0627 | 0.1987 | 0.3009    |
+| 0.0529        | 4.0498 | 1300 | 0.0623          | 0.0623 | 0.1970 | 0.3049    |
+| 0.0546        | 4.3614 | 1400 | 0.0624          | 0.0624 | 0.1962 | 0.3044    |
+| 0.0535        | 4.6729 | 1500 | 0.0623          | 0.0623 | 0.1972 | 0.3055    |
+| 0.0536        | 4.9844 | 1600 | 0.0622          | 0.0622 | 0.1968 | 0.3060    |
+
+
+### Framework versions
+
+- PEFT 0.13.2
+- Transformers 4.45.2
+- Pytorch 2.5.1+cu121
+- Datasets 3.1.0
 - Tokenizers 0.20.3