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--- |
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base_model: mistralai/Mistral-7B-Instruct-v0.2 |
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datasets: |
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- generator |
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library_name: peft |
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license: apache-2.0 |
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tags: |
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- trl |
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- sft |
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- generated_from_trainer |
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model-index: |
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- name: Translator_Eng_Tel_instruct |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# Translator_Eng_Tel_instruct |
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This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) on the generator dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2120 |
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## Model description |
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This model is a fine-tuned version of the Mistral 7B Instruct model aimed at translating English text to Telugu. It has been fine-tuned using the QLoRA 4-bit technique for instruction fine-tuning. |
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## Intended uses & limitations |
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This model is intended for translating English text to Telugu. It is recommended to use this model in environments that require high-quality translations between these two languages. |
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## Usage: |
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```bash |
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from peft import PeftModel, PeftConfig |
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from transformers import AutoModelForCausalLM |
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config = PeftConfig.from_pretrained("MRR24/Translator_Eng_Tel_instruct") |
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base_model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-Instruct-v0.2") |
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model = PeftModel.from_pretrained(base_model, "MRR24/Translator_Eng_Tel_instruct") |
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``` |
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## Training and evaluation data |
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The training dataset consists of 140k data points, while the testing dataset contains 16k data points. These datasets were meticulously curated to ensure the high-quality translation capability of the model. |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0005 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 8 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 2 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 0.2549 | 0.9992 | 956 | 0.2554 | |
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| 0.2138 | 1.9984 | 1912 | 0.2120 | |
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### Framework versions |
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- PEFT 0.10.0 |
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- Transformers 4.40.1 |
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- Pytorch 2.1.1+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |