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 +164 -150

README.md CHANGED Viewed

@@ -1,151 +1,165 @@
----
-library_name: peft
-license: apache-2.0
-base_model: Qwen/Qwen2.5-0.5B
-tags:
-- axolotl
-- generated_from_trainer
-model-index:
-- name: 0a929cd7-4abe-4be4-bfa0-d7da7d03b9b8
-  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: `0.4.1`
-```yaml
-adapter: lora
-base_model: Qwen/Qwen2.5-0.5B
-bf16: true
-chat_template: llama3
-dataset_prepared_path: null
-datasets:
-- data_files:
-  - 827d98d6f834ce6e_train_data.json
-  ds_type: json
-  format: custom
-  path: /workspace/input_data/827d98d6f834ce6e_train_data.json
-  type:
-    field_input: question
-    field_instruction: messages
-    field_output: model_response
-    format: '{instruction} {input}'
-    no_input_format: '{instruction}'
-    system_format: '{system}'
-    system_prompt: ''
-debug: null
-deepspeed: null
-early_stopping_patience: null
-eval_max_new_tokens: 256
-eval_table_size: null
-evals_per_epoch: 4
-flash_attention: false
-fp16: false
-fsdp: null
-fsdp_config: null
-gradient_accumulation_steps: 4
-gradient_checkpointing: true
-group_by_length: true
-hub_model_id: Dolboebina/0a929cd7-4abe-4be4-bfa0-d7da7d03b9b8
-hub_repo: null
-hub_strategy: checkpoint
-hub_token: null
-learning_rate: 0.0002
-load_in_4bit: true
-load_in_8bit: false
-local_rank: null
-logging_steps: 1
-lora_alpha: 64
-lora_dropout: 0.05
-lora_fan_in_fan_out: null
-lora_model_dir: null
-lora_r: 16
-lora_target_linear: true
-lr_scheduler: cosine
-max_steps: 10
-micro_batch_size: 2
-mlflow_experiment_name: /tmp/827d98d6f834ce6e_train_data.json
-model_type: AutoModelForCausalLM
-num_epochs: 1
-optimizer: adamw_bnb_8bit
-output_dir: miner_id_24
-pad_to_sequence_len: true
-resume_from_checkpoint: null
-sample_packing: true
-saves_per_epoch: 4
-sequence_len: 4096
-strict: false
-tf32: true
-tokenizer_type: AutoTokenizer
-train_on_inputs: false
-trust_remote_code: true
-val_set_size: 0.05
-wandb_entity: null
-wandb_mode: online
-wandb_name: 0a929cd7-4abe-4be4-bfa0-d7da7d03b9b8
-wandb_project: Gradients-On-Demand
-wandb_run: your_name
-wandb_runid: 0a929cd7-4abe-4be4-bfa0-d7da7d03b9b8
-warmup_steps: 10
-weight_decay: 0.01
-xformers_attention: false
-```
-</details><br>
-# 0a929cd7-4abe-4be4-bfa0-d7da7d03b9b8
-This model is a fine-tuned version of [Qwen/Qwen2.5-0.5B](https://huggingface.co/Qwen/Qwen2.5-0.5B) on the None dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.5901
-## 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: 0.0002
-- train_batch_size: 2
-- eval_batch_size: 2
-- seed: 42
-- gradient_accumulation_steps: 4
-- total_train_batch_size: 8
-- optimizer: Use OptimizerNames.ADAMW_BNB 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
-- training_steps: 10
-### Training results
-| Training Loss | Epoch  | Step | Validation Loss |
-|:-------------:|:------:|:----:|:---------------:|
-| 1.7006        | 0.0015 | 1    | 1.4715          |
-| 1.3025        | 0.0044 | 3    | 1.3203          |
-| 1.1745        | 0.0089 | 6    | 0.8342          |
-| 0.5756        | 0.0133 | 9    | 0.5901          |
-### Framework versions
-- PEFT 0.13.2
-- Transformers 4.46.0
-- Pytorch 2.5.0+cu124
-- Datasets 3.0.1
 - Tokenizers 0.20.1

+---
+library_name: peft
+license: apache-2.0
+base_model: Qwen/Qwen2.5-0.5B
+tags:
+- axolotl
+- generated_from_trainer
+language:
+- zho
+- eng
+- fra
+- spa
+- por
+- deu
+- ita
+- rus
+- jpn
+- kor
+- vie
+- tha
+- ara
+model-index:
+- name: 0a929cd7-4abe-4be4-bfa0-d7da7d03b9b8
+  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: `0.4.1`
+```yaml
+adapter: lora
+base_model: Qwen/Qwen2.5-0.5B
+bf16: true
+chat_template: llama3
+dataset_prepared_path: null
+datasets:
+- data_files:
+  - 827d98d6f834ce6e_train_data.json
+  ds_type: json
+  format: custom
+  path: /workspace/input_data/827d98d6f834ce6e_train_data.json
+  type:
+    field_input: question
+    field_instruction: messages
+    field_output: model_response
+    format: '{instruction} {input}'
+    no_input_format: '{instruction}'
+    system_format: '{system}'
+    system_prompt: ''
+debug: null
+deepspeed: null
+early_stopping_patience: null
+eval_max_new_tokens: 256
+eval_table_size: null
+evals_per_epoch: 4
+flash_attention: false
+fp16: false
+fsdp: null
+fsdp_config: null
+gradient_accumulation_steps: 4
+gradient_checkpointing: true
+group_by_length: true
+hub_model_id: Dolboebina/0a929cd7-4abe-4be4-bfa0-d7da7d03b9b8
+hub_repo: null
+hub_strategy: checkpoint
+hub_token: null
+learning_rate: 0.0002
+load_in_4bit: true
+load_in_8bit: false
+local_rank: null
+logging_steps: 1
+lora_alpha: 64
+lora_dropout: 0.05
+lora_fan_in_fan_out: null
+lora_model_dir: null
+lora_r: 16
+lora_target_linear: true
+lr_scheduler: cosine
+max_steps: 10
+micro_batch_size: 2
+mlflow_experiment_name: /tmp/827d98d6f834ce6e_train_data.json
+model_type: AutoModelForCausalLM
+num_epochs: 1
+optimizer: adamw_bnb_8bit
+output_dir: miner_id_24
+pad_to_sequence_len: true
+resume_from_checkpoint: null
+sample_packing: true
+saves_per_epoch: 4
+sequence_len: 4096
+strict: false
+tf32: true
+tokenizer_type: AutoTokenizer
+train_on_inputs: false
+trust_remote_code: true
+val_set_size: 0.05
+wandb_entity: null
+wandb_mode: online
+wandb_name: 0a929cd7-4abe-4be4-bfa0-d7da7d03b9b8
+wandb_project: Gradients-On-Demand
+wandb_run: your_name
+wandb_runid: 0a929cd7-4abe-4be4-bfa0-d7da7d03b9b8
+warmup_steps: 10
+weight_decay: 0.01
+xformers_attention: false
+```
+</details><br>
+# 0a929cd7-4abe-4be4-bfa0-d7da7d03b9b8
+This model is a fine-tuned version of [Qwen/Qwen2.5-0.5B](https://huggingface.co/Qwen/Qwen2.5-0.5B) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5901
+## 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: 0.0002
+- train_batch_size: 2
+- eval_batch_size: 2
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 8
+- optimizer: Use OptimizerNames.ADAMW_BNB 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
+- training_steps: 10
+### Training results
+| Training Loss | Epoch  | Step | Validation Loss |
+|:-------------:|:------:|:----:|:---------------:|
+| 1.7006        | 0.0015 | 1    | 1.4715          |
+| 1.3025        | 0.0044 | 3    | 1.3203          |
+| 1.1745        | 0.0089 | 6    | 0.8342          |
+| 0.5756        | 0.0133 | 9    | 0.5901          |
+### Framework versions
+- PEFT 0.13.2
+- Transformers 4.46.0
+- Pytorch 2.5.0+cu124
+- Datasets 3.0.1
 - Tokenizers 0.20.1