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--- |
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base_model: openaccess-ai-collective/tiny-mistral |
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library_name: peft |
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tags: |
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- generated_from_trainer |
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- fine-tuning |
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- text-generation |
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model-index: |
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- name: tiny-mistral-alpaca-finance |
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results: [] |
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datasets: |
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- gbharti/finance-alpaca |
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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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# Tiny Mistral fine-tuned on finance dataset |
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This model is a fine-tuned version of the `openaccess-ai-collective/tiny-mistral` language model. |
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It has been fine-tuned on a specialized finance dataset using Parameter-Efficient Fine-Tuning (PEFT) with Low-Rank Adaptation (LoRA). |
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The model is designed to generate responses based on financial instructions and contexts. |
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## Intended uses & limitations |
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This model is intended for text generation tasks specifically related to financial instructions and contexts. |
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It can be used for generating responses based on given financial prompts. |
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**Limitations:** |
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- The model may not perform well on financial topics not covered in the training data. |
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- The quality of responses may vary depending on the specificity and complexity of the financial queries. |
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- The model may generate responses that are not factually accurate or may include biases present in the training data. |
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## Training and evaluation data |
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The model was fine-tuned on the `gbharti/finance-alpaca` dataset, which includes financial instructions and outputs. |
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The dataset was processed to format instructions with or without additional context. |
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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: 0.0002 |
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- train_batch_size: 4 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 32 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 100 |
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- num_epochs: 2 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 1.3155 | 0.2580 | 500 | 1.3207 | |
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| 1.1306 | 0.5160 | 1000 | 1.1318 | |
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| 0.9935 | 0.7739 | 1500 | 0.9970 | |
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| 0.7188 | 1.0319 | 2000 | 0.8934 | |
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| 0.6962 | 1.2899 | 2500 | 0.8238 | |
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| 0.6427 | 1.5479 | 3000 | 0.7610 | |
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| 0.6014 | 1.8059 | 3500 | 0.7193 | |
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### Framework versions |
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- PEFT 0.12.0 |
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- Transformers 4.42.4 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
