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

@@ -1,82 +1,93 @@
----
-library_name: transformers
-license: apache-2.0
-base_model: Qwen/Qwen2.5-32B-Instruct
-tags:
-- alignment-handbook
-- trl
-- dpo
-- generated_from_trainer
-- trl
-- dpo
-- generated_from_trainer
-datasets:
-- tanliboy/orca_dpo_pairs
-model-index:
-- name: lambda-qwen2.5-32b-dpo-test
-  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. -->
-
-# lambda-qwen2.5-32b-dpo-test
-
-This model is a fine-tuned version of [Qwen/Qwen2.5-32B-Instruct](https://huggingface.co/Qwen/Qwen2.5-32B-Instruct) on the tanliboy/orca_dpo_pairs dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.0003
-- Rewards/chosen: -10.1618
-- Rewards/rejected: -26.1150
-- Rewards/accuracies: 1.0
-- Rewards/margins: 15.9532
-- Logps/rejected: -3049.5271
-- Logps/chosen: -1372.8903
-- Logits/rejected: -0.3154
-- Logits/chosen: -0.0600
-
-## 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-07
-- train_batch_size: 2
-- eval_batch_size: 2
-- seed: 42
-- distributed_type: multi-GPU
-- num_devices: 8
-- gradient_accumulation_steps: 2
-- total_train_batch_size: 32
-- total_eval_batch_size: 16
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-- lr_scheduler_type: cosine
-- lr_scheduler_warmup_ratio: 0.1
-- num_epochs: 1
-
-### Training results
-
-| Training Loss | Epoch  | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
-|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
-| 0.0103        | 0.2618 | 100  | 0.0060          | -8.5159        | -18.7731         | 1.0                | 10.2572         | -2315.3333     | -1208.2968   | -0.5485         | -0.2481       |
-| 0.0005        | 0.5236 | 200  | 0.0005          | -9.9255        | -24.9117         | 1.0                | 14.9862         | -2929.1948     | -1349.2588   | -0.3723         | -0.0661       |
-| 0.0005        | 0.7853 | 300  | 0.0004          | -10.0873       | -25.9319         | 1.0                | 15.8446         | -3031.2175     | -1365.4342   | -0.2882         | -0.0014       |
-
-
-### Framework versions
-
-- Transformers 4.44.2
-- Pytorch 2.4.0+cu121
-- Datasets 2.19.1
-- Tokenizers 0.19.1
+---
+library_name: transformers
+license: apache-2.0
+base_model: Qwen/Qwen2.5-32B-Instruct
+tags:
+- alignment-handbook
+- trl
+- dpo
+- generated_from_trainer
+datasets:
+- tanliboy/orca_dpo_pairs
+language:
+- zho
+- eng
+- fra
+- spa
+- por
+- deu
+- ita
+- rus
+- jpn
+- kor
+- vie
+- tha
+- ara
+model-index:
+- name: lambda-qwen2.5-32b-dpo-test
+  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. -->
+
+# lambda-qwen2.5-32b-dpo-test
+
+This model is a fine-tuned version of [Qwen/Qwen2.5-32B-Instruct](https://huggingface.co/Qwen/Qwen2.5-32B-Instruct) on the tanliboy/orca_dpo_pairs dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0003
+- Rewards/chosen: -10.1618
+- Rewards/rejected: -26.1150
+- Rewards/accuracies: 1.0
+- Rewards/margins: 15.9532
+- Logps/rejected: -3049.5271
+- Logps/chosen: -1372.8903
+- Logits/rejected: -0.3154
+- Logits/chosen: -0.0600
+
+## 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-07
+- train_batch_size: 2
+- eval_batch_size: 2
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 8
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 32
+- total_eval_batch_size: 16
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 1
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
+|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
+| 0.0103        | 0.2618 | 100  | 0.0060          | -8.5159        | -18.7731         | 1.0                | 10.2572         | -2315.3333     | -1208.2968   | -0.5485         | -0.2481       |
+| 0.0005        | 0.5236 | 200  | 0.0005          | -9.9255        | -24.9117         | 1.0                | 14.9862         | -2929.1948     | -1349.2588   | -0.3723         | -0.0661       |
+| 0.0005        | 0.7853 | 300  | 0.0004          | -10.0873       | -25.9319         | 1.0                | 15.8446         | -3031.2175     | -1365.4342   | -0.2882         | -0.0014       |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.4.0+cu121
+- Datasets 2.19.1
+- Tokenizers 0.19.1