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Mistral-7B-v0.1_cola_original2
thrunlab/Mistral-7B-v0.1_cola_original2
Mistral-7B-v0.1_cola_original2 is a machine learning model from thrunlab. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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Public
Updated Jan 18, 2024
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At a glance
- License
- apache-2.0
- Access
- Public
- Created
- Jan 18, 2024
- Updated
- Jan 18, 2024
- SHA
- 876a477d
Base models
Model card
From the Hugging Face model README
<!-- 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. -->
Mistral-7B-v0.1_cola_original2
This model is a fine-tuned version of mistralai/Mistral-7B-v0.1 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3773
- Accuracy: {'accuracy': 0.8539719626168224}
- Matthews Correlation: 0.6454
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: 1e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 2
- distributed_type: multi-GPU
- num_devices: 6
- total_train_batch_size: 384
- total_eval_batch_size: 384
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 750
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Matthews Correlation |
|---|---|---|---|---|---|
| 0.4986 | 2.38 | 50 | 0.5042 | {'accuracy': 0.7938638542665388} | 0.4836 |
| 0.3193 | 4.76 | 100 | 0.4002 | {'accuracy': 0.8264621284755513} | 0.6029 |
| 0.2489 | 7.14 | 150 | 0.3795 | {'accuracy': 0.8389261744966443} | 0.6123 |
| 0.1258 | 9.52 | 200 | 0.4322 | {'accuracy': 0.8418024928092043} | 0.6284 |
| 0.0625 | 11.9 | 250 | 0.5921 | {'accuracy': 0.8427612655800575} | 0.6258 |
| 0.0251 | 14.29 | 300 | 0.8451 | {'accuracy': 0.8446788111217641} | 0.6248 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
- License
- apache-2.0
- Created
- Jan 18, 2024
- Updated
- Jan 18, 2024