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 +161 -147

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@@ -1,147 +1,161 @@
----
-library_name: transformers
-base_model: Qwen/Qwen2.5-14B
-tags:
-- axolotl
-- generated_from_trainer
-model-index:
-- name: medius-erebus-magnum-14b
-  results: []
----
-### exl2 quant (measurement.json in main branch)
----
-### check revisions for quants
----
-[<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
-base_model: /workspace/medius-erebus
-model_type: AutoModelForCausalLM
-tokenizer_type: AutoTokenizer
-hub_model_id: magnum-erebus-14b-v1
-hub_strategy: "all_checkpoints"
-push_dataset_to_hub:
-hf_use_auth_token: true
-plugins:
-  - axolotl.integrations.liger.LigerPlugin
-liger_rope: true
-liger_rms_norm: true
-liger_swiglu: true
-liger_fused_linear_cross_entropy: true
-load_in_8bit: false
-load_in_4bit: false
-strict: false
-datasets:
-  - path: anthracite-core/c2_logs_32k_llama3_qwen2_v1.2
-    type: sharegpt
-  - path: anthracite-org/kalo-opus-instruct-22k-no-refusal
-    type: sharegpt
-  - path: lodrick-the-lafted/kalo-opus-instruct-3k-filtered
-    type: sharegpt
-  - path: anthracite-org/nopm_claude_writing_fixed
-    type: sharegpt
-  - path: anthracite-org/kalo_opus_misc_240827
-    type: sharegpt
-  - path: anthracite-org/kalo_misc_part2
-    type: sharegpt
-chat_template: chatml
-shuffle_merged_datasets: true
-default_system_message: "You are an assistant that responds to the user."
-dataset_prepared_path: /workspace/data/magnum-14b-data
-val_set_size: 0.0
-output_dir: /workspace/data/magnum-erebus-14b-fft
-sequence_len: 32768
-sample_packing: true
-pad_to_sequence_len: true
-adapter:
-lora_model_dir:
-lora_r:
-lora_alpha:
-lora_dropout:
-lora_target_linear:
-lora_fan_in_fan_out:
-wandb_project: 14b-magnum-fft
-wandb_entity:
-wandb_watch:
-wandb_name: v4-r2-erebus-attempt-1
-wandb_log_model:
-gradient_accumulation_steps: 1
-micro_batch_size: 2
-num_epochs: 2
-optimizer: adamw_bnb_8bit
-lr_scheduler: cosine
-learning_rate: 0.000008
-train_on_inputs: false
-group_by_length: false
-bf16: auto
-fp16:
-tf32: false
-gradient_checkpointing: unsloth
-early_stopping_patience:
-resume_from_checkpoint:
-local_rank:
-logging_steps: 1
-xformers_attention:
-flash_attention: true
-warmup_steps: 40
-evals_per_epoch:
-eval_table_size:
-eval_max_new_tokens:
-saves_per_epoch: 2
-debug:
-deepspeed: deepspeed_configs/zero3_bf16.json
-weight_decay: 0.1
-fsdp:
-fsdp_config:
-special_tokens:
-```
-</details><br>
-# medius-erebus-magnum
-## Training procedure
-### Training hyperparameters
-The following hyperparameters were used during training:
-- learning_rate: 8e-06
-- train_batch_size: 2
-- eval_batch_size: 2
-- seed: 42
-- distributed_type: multi-GPU
-- num_devices: 8
-- total_train_batch_size: 16
-- total_eval_batch_size: 16
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-- lr_scheduler_type: cosine
-- lr_scheduler_warmup_steps: 40
-- num_epochs: 2
-### Training results
-### Framework versions
-- Transformers 4.45.1
-- Pytorch 2.3.1+cu121
-- Datasets 2.21.0
-- Tokenizers 0.20.0

+---
+library_name: transformers
+base_model: Qwen/Qwen2.5-14B
+tags:
+- axolotl
+- generated_from_trainer
+language:
+- zho
+- eng
+- fra
+- spa
+- por
+- deu
+- ita
+- rus
+- jpn
+- kor
+- vie
+- tha
+- ara
+model-index:
+- name: medius-erebus-magnum-14b
+  results: []
+---
+### exl2 quant (measurement.json in main branch)
+---
+### check revisions for quants
+---
+[<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
+base_model: /workspace/medius-erebus
+model_type: AutoModelForCausalLM
+tokenizer_type: AutoTokenizer
+hub_model_id: magnum-erebus-14b-v1
+hub_strategy: "all_checkpoints"
+push_dataset_to_hub:
+hf_use_auth_token: true
+plugins:
+  - axolotl.integrations.liger.LigerPlugin
+liger_rope: true
+liger_rms_norm: true
+liger_swiglu: true
+liger_fused_linear_cross_entropy: true
+load_in_8bit: false
+load_in_4bit: false
+strict: false
+datasets:
+  - path: anthracite-core/c2_logs_32k_llama3_qwen2_v1.2
+    type: sharegpt
+  - path: anthracite-org/kalo-opus-instruct-22k-no-refusal
+    type: sharegpt
+  - path: lodrick-the-lafted/kalo-opus-instruct-3k-filtered
+    type: sharegpt
+  - path: anthracite-org/nopm_claude_writing_fixed
+    type: sharegpt
+  - path: anthracite-org/kalo_opus_misc_240827
+    type: sharegpt
+  - path: anthracite-org/kalo_misc_part2
+    type: sharegpt
+chat_template: chatml
+shuffle_merged_datasets: true
+default_system_message: "You are an assistant that responds to the user."
+dataset_prepared_path: /workspace/data/magnum-14b-data
+val_set_size: 0.0
+output_dir: /workspace/data/magnum-erebus-14b-fft
+sequence_len: 32768
+sample_packing: true
+pad_to_sequence_len: true
+adapter:
+lora_model_dir:
+lora_r:
+lora_alpha:
+lora_dropout:
+lora_target_linear:
+lora_fan_in_fan_out:
+wandb_project: 14b-magnum-fft
+wandb_entity:
+wandb_watch:
+wandb_name: v4-r2-erebus-attempt-1
+wandb_log_model:
+gradient_accumulation_steps: 1
+micro_batch_size: 2
+num_epochs: 2
+optimizer: adamw_bnb_8bit
+lr_scheduler: cosine
+learning_rate: 0.000008
+train_on_inputs: false
+group_by_length: false
+bf16: auto
+fp16:
+tf32: false
+gradient_checkpointing: unsloth
+early_stopping_patience:
+resume_from_checkpoint:
+local_rank:
+logging_steps: 1
+xformers_attention:
+flash_attention: true
+warmup_steps: 40
+evals_per_epoch:
+eval_table_size:
+eval_max_new_tokens:
+saves_per_epoch: 2
+debug:
+deepspeed: deepspeed_configs/zero3_bf16.json
+weight_decay: 0.1
+fsdp:
+fsdp_config:
+special_tokens:
+```
+</details><br>
+# medius-erebus-magnum
+## Training procedure
+### Training hyperparameters
+The following hyperparameters were used during training:
+- learning_rate: 8e-06
+- train_batch_size: 2
+- eval_batch_size: 2
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 8
+- total_train_batch_size: 16
+- total_eval_batch_size: 16
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 40
+- num_epochs: 2
+### Training results
+### Framework versions
+- Transformers 4.45.1
+- Pytorch 2.3.1+cu121
+- Datasets 2.21.0
+- Tokenizers 0.20.0