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

@@ -1,211 +1,222 @@
----
-library_name: transformers
-license: apache-2.0
-base_model: Qwen/Qwen2.5-0.5B-Instruct
-tags:
-- generated_from_trainer
-- axolotl
-language:
-- it
-- en
-pipeline_tag: text-generation
-datasets:
-- ReDiX/everyday-conversations-ita
-- ReDiX/dataforge-cleaned
----
-
-# Qwen2.5-0.5B-Instruct-ITA
-
-This model is a fine-tuned version of [Qwen/Qwen2.5-0.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-0.5B-Instruct) on the [ReDiX/DataForge](https://huggingface.co/datasets/ReDiX/DataForge) dataset.
-It achieves the following results on the evaluation set:
-- Loss: 1.4100
-
-## Model description
-
-This model is an example of finetuning a sLLM. Italian eval improved and the model learned as espected from the training data
-
-## Intended uses & limitations
-
-More information needed
-
-## Training and evaluation data
-
-
-|   Tasks    |Version|Filter|n-shot| Metric |   |Value |   |Stderr|
-|------------|------:|------|-----:|--------|---|-----:|---|-----:|
-|arc_it      |      2|none  |     0|acc     |↑  |0.2378|±  |0.0125|
-|            |       |none  |     0|acc_norm|↑  |0.2823|±  |0.0132|
-|hellaswag_it|      1|none  |     0|acc     |↑  |0.3163|±  |0.0049|
-|            |       |none  |     0|acc_norm|↑  |0.3800|±  |0.0051|
-|m_mmlu_it   |      0|none  |     5|acc     |↑  |0.381 |±  |0.0042|
-
-## Training procedure
-
-### Training hyperparameters
-
-The following hyperparameters were used during training:
-- learning_rate: 0.0001
-- train_batch_size: 4
-- eval_batch_size: 4
-- seed: 42
-- gradient_accumulation_steps: 4
-- total_train_batch_size: 16
-- optimizer: Use adamw_bnb_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: 10
-- num_epochs: 2
-
-
-[<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: `0.5.0`
-```yaml
-base_model: Qwen/Qwen2.5-0.5B-Instruct
-
-load_in_8bit: false
-load_in_4bit: false
-strict: false
-
-datasets:
-  - path: ./dataforge
-    type: chat_template
-
-    field_messages: conversations
-    message_field_role: from
-    message_field_content: value
-
-# chat_template: chatml
-dataset_prepared_path: last_run_prepared
-val_set_size: 0.1
-output_dir: ./outputs/qwen05B
-
-unfrozen_parameters:
-- ^lm_head.weight$
-- ^model.embed_tokens.weight$
-# mlp.down_proj layers
-- model.layers.0.mlp.down_proj
-- model.layers.23.mlp.down_proj
-- model.layers.1.mlp.down_proj
-- model.layers.16.mlp.down_proj
-- model.layers.4.mlp.down_proj
-- model.layers.17.mlp.down_proj
-# mlp.gate_proj layers
-- model.layers.0.mlp.gate_proj
-- model.layers.1.mlp.gate_proj
-- model.layers.2.mlp.gate_proj
-- model.layers.3.mlp.gate_proj
-- model.layers.4.mlp.gate_proj
-- model.layers.7.mlp.gate_proj
-# mlp.up_proj layers
-- model.layers.1.mlp.up_proj
-- model.layers.0.mlp.up_proj
-- model.layers.3.mlp.up_proj
-- model.layers.4.mlp.up_proj
-- model.layers.7.mlp.up_proj
-- model.layers.9.mlp.up_proj
-# self_attn.k_proj layers
-- model.layers.18.self_attn.k_proj
-- model.layers.7.self_attn.k_proj
-- model.layers.19.self_attn.k_proj
-- model.layers.2.self_attn.k_proj
-- model.layers.6.self_attn.k_proj
-- model.layers.9.self_attn.k_proj
-# self_attn.o_proj layers
-- model.layers.16.self_attn.o_proj
-- model.layers.19.self_attn.o_proj
-- model.layers.0.self_attn.o_proj
-- model.layers.20.self_attn.o_proj
-- model.layers.4.self_attn.o_proj
-- model.layers.3.self_attn.o_proj
-# self_attn.q_proj layers
-- model.layers.13.self_attn.q_proj
-- model.layers.16.self_attn.q_proj
-- model.layers.21.self_attn.q_proj
-- model.layers.11.self_attn.q_proj
-- model.layers.15.self_attn.q_proj
-- model.layers.6.self_attn.q_proj
-# self_attn.v_proj layers
-- model.layers.2.self_attn.v_proj
-- model.layers.3.self_attn.v_proj
-- model.layers.4.self_attn.v_proj
-- model.layers.5.self_attn.v_proj
-- model.layers.7.self_attn.v_proj
-- model.layers.8.self_attn.v_proj
-
-
-
-sequence_len: 4096
-sample_packing: true
-eval_sample_packing: true
-pad_to_sequence_len: true
-
-
-wandb_project: axolotl
-wandb_entity:
-wandb_watch:
-wandb_name: qwen2.5-0.5B
-wandb_log_model:
-
-gradient_accumulation_steps: 4
-micro_batch_size: 4
-num_epochs: 2
-optimizer: adamw_bnb_8bit
-lr_scheduler: cosine
-learning_rate: 1.0e-04
-
-train_on_inputs: false
-group_by_length: false
-bf16: true
-fp16: 
-tf32: false
-
-gradient_checkpointing: true
-early_stopping_patience:
-resume_from_checkpoint:
-local_rank:
-logging_steps: 5
-xformers_attention:
-flash_attention: true
-
-
-warmup_steps: 10
-evals_per_epoch: 4
-eval_table_size:
-eval_max_new_tokens: 128
-saves_per_epoch: 1
-debug:
-deepspeed:
-weight_decay: 0.0
-fsdp:
-fsdp_config:
-special_tokens:
-  pad_token: "<|im_end|>"
-  eos_token: "<|im_end|>"
-
-
-```
-
-</details><br>
-
-
-### Training results
-
-| Training Loss | Epoch  | Step | Validation Loss |
-|:-------------:|:------:|:----:|:---------------:|
-| No log        | 0.0013 | 1    | 1.7855          |
-| 1.2567        | 0.2504 | 194  | 1.5639          |
-| 1.2551        | 0.5008 | 388  | 1.4980          |
-| 1.1845        | 0.7512 | 582  | 1.4501          |
-| 1.3178        | 1.0019 | 776  | 1.4252          |
-| 1.06          | 1.2523 | 970  | 1.4187          |
-| 1.0697        | 1.5027 | 1164 | 1.4116          |
-| 1.0362        | 1.7531 | 1358 | 1.4100          |
-
-
-### Framework versions
-
-- Transformers 4.46.2
-- Pytorch 2.5.1+cu124
-- Datasets 3.1.0
+---
+library_name: transformers
+license: apache-2.0
+base_model: Qwen/Qwen2.5-0.5B-Instruct
+tags:
+- generated_from_trainer
+- axolotl
+language:
+- zho
+- eng
+- fra
+- spa
+- por
+- deu
+- ita
+- rus
+- jpn
+- kor
+- vie
+- tha
+- ara
+pipeline_tag: text-generation
+datasets:
+- ReDiX/everyday-conversations-ita
+- ReDiX/dataforge-cleaned
+---
+
+# Qwen2.5-0.5B-Instruct-ITA
+
+This model is a fine-tuned version of [Qwen/Qwen2.5-0.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-0.5B-Instruct) on the [ReDiX/DataForge](https://huggingface.co/datasets/ReDiX/DataForge) dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.4100
+
+## Model description
+
+This model is an example of finetuning a sLLM. Italian eval improved and the model learned as espected from the training data
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+
+|   Tasks    |Version|Filter|n-shot| Metric |   |Value |   |Stderr|
+|------------|------:|------|-----:|--------|---|-----:|---|-----:|
+|arc_it      |      2|none  |     0|acc     |↑  |0.2378|±  |0.0125|
+|            |       |none  |     0|acc_norm|↑  |0.2823|±  |0.0132|
+|hellaswag_it|      1|none  |     0|acc     |↑  |0.3163|±  |0.0049|
+|            |       |none  |     0|acc_norm|↑  |0.3800|±  |0.0051|
+|m_mmlu_it   |      0|none  |     5|acc     |↑  |0.381 |±  |0.0042|
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 0.0001
+- train_batch_size: 4
+- eval_batch_size: 4
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 16
+- optimizer: Use adamw_bnb_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: 10
+- num_epochs: 2
+
+
+[<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: `0.5.0`
+```yaml
+base_model: Qwen/Qwen2.5-0.5B-Instruct
+
+load_in_8bit: false
+load_in_4bit: false
+strict: false
+
+datasets:
+  - path: ./dataforge
+    type: chat_template
+
+    field_messages: conversations
+    message_field_role: from
+    message_field_content: value
+
+# chat_template: chatml
+dataset_prepared_path: last_run_prepared
+val_set_size: 0.1
+output_dir: ./outputs/qwen05B
+
+unfrozen_parameters:
+- ^lm_head.weight$
+- ^model.embed_tokens.weight$
+# mlp.down_proj layers
+- model.layers.0.mlp.down_proj
+- model.layers.23.mlp.down_proj
+- model.layers.1.mlp.down_proj
+- model.layers.16.mlp.down_proj
+- model.layers.4.mlp.down_proj
+- model.layers.17.mlp.down_proj
+# mlp.gate_proj layers
+- model.layers.0.mlp.gate_proj
+- model.layers.1.mlp.gate_proj
+- model.layers.2.mlp.gate_proj
+- model.layers.3.mlp.gate_proj
+- model.layers.4.mlp.gate_proj
+- model.layers.7.mlp.gate_proj
+# mlp.up_proj layers
+- model.layers.1.mlp.up_proj
+- model.layers.0.mlp.up_proj
+- model.layers.3.mlp.up_proj
+- model.layers.4.mlp.up_proj
+- model.layers.7.mlp.up_proj
+- model.layers.9.mlp.up_proj
+# self_attn.k_proj layers
+- model.layers.18.self_attn.k_proj
+- model.layers.7.self_attn.k_proj
+- model.layers.19.self_attn.k_proj
+- model.layers.2.self_attn.k_proj
+- model.layers.6.self_attn.k_proj
+- model.layers.9.self_attn.k_proj
+# self_attn.o_proj layers
+- model.layers.16.self_attn.o_proj
+- model.layers.19.self_attn.o_proj
+- model.layers.0.self_attn.o_proj
+- model.layers.20.self_attn.o_proj
+- model.layers.4.self_attn.o_proj
+- model.layers.3.self_attn.o_proj
+# self_attn.q_proj layers
+- model.layers.13.self_attn.q_proj
+- model.layers.16.self_attn.q_proj
+- model.layers.21.self_attn.q_proj
+- model.layers.11.self_attn.q_proj
+- model.layers.15.self_attn.q_proj
+- model.layers.6.self_attn.q_proj
+# self_attn.v_proj layers
+- model.layers.2.self_attn.v_proj
+- model.layers.3.self_attn.v_proj
+- model.layers.4.self_attn.v_proj
+- model.layers.5.self_attn.v_proj
+- model.layers.7.self_attn.v_proj
+- model.layers.8.self_attn.v_proj
+
+
+
+sequence_len: 4096
+sample_packing: true
+eval_sample_packing: true
+pad_to_sequence_len: true
+
+
+wandb_project: axolotl
+wandb_entity:
+wandb_watch:
+wandb_name: qwen2.5-0.5B
+wandb_log_model:
+
+gradient_accumulation_steps: 4
+micro_batch_size: 4
+num_epochs: 2
+optimizer: adamw_bnb_8bit
+lr_scheduler: cosine
+learning_rate: 1.0e-04
+
+train_on_inputs: false
+group_by_length: false
+bf16: true
+fp16: 
+tf32: false
+
+gradient_checkpointing: true
+early_stopping_patience:
+resume_from_checkpoint:
+local_rank:
+logging_steps: 5
+xformers_attention:
+flash_attention: true
+
+
+warmup_steps: 10
+evals_per_epoch: 4
+eval_table_size:
+eval_max_new_tokens: 128
+saves_per_epoch: 1
+debug:
+deepspeed:
+weight_decay: 0.0
+fsdp:
+fsdp_config:
+special_tokens:
+  pad_token: "<|im_end|>"
+  eos_token: "<|im_end|>"
+
+
+```
+
+</details><br>
+
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss |
+|:-------------:|:------:|:----:|:---------------:|
+| No log        | 0.0013 | 1    | 1.7855          |
+| 1.2567        | 0.2504 | 194  | 1.5639          |
+| 1.2551        | 0.5008 | 388  | 1.4980          |
+| 1.1845        | 0.7512 | 582  | 1.4501          |
+| 1.3178        | 1.0019 | 776  | 1.4252          |
+| 1.06          | 1.2523 | 970  | 1.4187          |
+| 1.0697        | 1.5027 | 1164 | 1.4116          |
+| 1.0362        | 1.7531 | 1358 | 1.4100          |
+
+
+### Framework versions
+
+- Transformers 4.46.2
+- Pytorch 2.5.1+cu124
+- Datasets 3.1.0
 - Tokenizers 0.20.3