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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: Qwen/Qwen2.5-7B-Instruct-1M |
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tags: |
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- sanskrit |
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- translation |
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- qwen |
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- axolotl |
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datasets: |
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- diabolic6045/Sanskrit-llama |
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model-index: |
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- name: Sanskrit-qwen-7B-Translate |
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results: [] |
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--- |
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# Sanskrit-qwen-7B-Translate |
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This model is a fine-tuned version of [Qwen/Qwen2.5-7B-Instruct-1M](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct-1M) optimized for Sanskrit language tasks. |
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## Model Description |
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This is a merged version of a fine-tuned Qwen 2.5 7B model, specifically trained for Sanskrit language understanding and translation tasks. The model has been trained on a custom Sanskrit dataset to enhance its capabilities in handling Sanskrit text. |
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## Intended Uses & Limitations |
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### Intended Uses |
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- Sanskrit text understanding and generation |
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- Sanskrit-English translation tasks |
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- Sanskrit language processing |
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### Limitations |
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- Performance may vary based on the complexity of Sanskrit text |
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- Model should be used within ethical and legal guidelines |
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## Training Data |
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The model was trained on the [diabolic6045/Sanskrit-llama](https://huggingface.co/datasets/diabolic6045/Sanskrit-llama) dataset. |
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## Training Procedure |
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### Training Details |
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- Base Model: Qwen/Qwen2.5-7B-Instruct-1M |
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- Training Type: Fine-tuning |
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- Hardware: Multi-GPU setup |
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- Training Parameters: |
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- Learning Rate: 2e-05 |
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- Epochs: 1 |
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- Batch Size: 2 (total) |
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- Optimizer: AdamW |
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- LR Scheduler: Cosine with warmup |
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## Framework Versions |
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- Transformers 4.49.0 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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[<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) |
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<details><summary>See axolotl config</summary> |
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axolotl version: `0.8.0.dev0` |
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```yaml |
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base_model: Qwen/Qwen2.5-7B-Instruct-1M |
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load_in_8bit: false |
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load_in_4bit: true |
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strict: false |
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datasets: |
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- path: diabolic6045/Sanskrit-llama |
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type: alpaca |
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dataset_prepared_path: |
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val_set_size: 0 |
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output_dir: ./outputs/qlora-out |
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adapter: qlora |
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lora_model_dir: |
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sequence_len: 1024 |
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sample_packing: true |
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eval_sample_packing: false |
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pad_to_sequence_len: true |
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lora_r: 32 |
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lora_alpha: 16 |
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lora_dropout: 0.05 |
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lora_target_modules: |
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lora_target_linear: true |
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lora_fan_in_fan_out: |
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hub_model_id: Sanskrit-qwen-8B |
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wandb_project: संस्कृतम्-llama |
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wandb_entity: |
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wandb_watch: all |
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wandb_name: संस्कृतम्-llama |
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wandb_log_model: |
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gradient_accumulation_steps: 1 |
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micro_batch_size: 1 |
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num_epochs: 1 |
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optimizer: paged_adamw_8bit |
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lr_scheduler: cosine |
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cosine_min_lr_ratio: 0.2 |
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learning_rate: 2e-5 |
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train_on_inputs: false |
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group_by_length: false |
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bf16: false |
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fp16: |
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tf32: false |
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gradient_checkpointing: true |
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early_stopping_patience: |
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resume_from_checkpoint: |
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local_rank: |
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logging_steps: 1 |
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xformers_attention: |
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flash_attention: false |
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#gpu_memory_limit: 20GiB |
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#lora_on_cpu: true |
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warmup_steps: 10 |
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evals_per_epoch: 4 |
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saves_per_epoch: 1 |
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debug: |
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deepspeed: deepspeed_configs/zero1.json |
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weight_decay: 0.0 |
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special_tokens: |
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pad_token: <|end_of_text|> |
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``` |
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</details><br> |
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## License |
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This model is released under the Apache 2.0 license. |
