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Mistral_Sparse_refined_web_50p_2024-03-28
thrunlab/Mistral_Sparse_refined_web_50p_2024-03-28
Mistral_Sparse_refined_web_50p_2024-03-28 is a text generation model from thrunlab. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Generation
- Library
- transformers
- License
- apache-2.0
- Model type
- sparse_mistral
- Access
- Public
- Created
- Mar 28, 2024
- Updated
- Mar 29, 2024
- SHA
- 975ed7db
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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_Sparse_refined_web_50p_2024-03-28
This model is a fine-tuned version of mistralai/Mistral-7B-v0.1 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.3726
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: 1
- eval_batch_size: 1
- seed: 0
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- total_eval_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 100
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.1889 | 0.0 | 25 | 2.4136 |
| 2.3169 | 0.01 | 50 | 2.4039 |
| 2.2154 | 0.01 | 75 | 2.3955 |
| 2.3394 | 0.02 | 100 | 2.3903 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
- Task
- Text Generation
- Library
- transformers
- Type
- sparse_mistral
- License
- apache-2.0
- Created
- Mar 28, 2024
- Updated
- Mar 29, 2024