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mistral-journal-finetune
baptistecolle/mistral-journal-finetune
mistral-journal-finetune is a machine learning model from baptistecolle. 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. --
Access
Public
Updated Nov 13, 2023
Repo size
340 MB
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At a glance
- License
- apache-2.0
- Access
- Public
- Created
- Nov 13, 2023
- Updated
- Nov 13, 2023
- SHA
- d629ba33
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-journal-finetune
This model is a fine-tuned version of Open-Orca/Mistral-7B-OpenOrca on an unknown dataset. It achieves the following results on the evaluation set:
- eval_loss: 2.0307
- eval_runtime: 98.0084
- eval_samples_per_second: 0.745
- eval_steps_per_second: 0.102
- epoch: 1.2
- step: 175
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: 2.5e-05
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1
- training_steps: 500
Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.0.0
- Datasets 2.14.6
- Tokenizers 0.14.1
- License
- apache-2.0
- Created
- Nov 13, 2023
- Updated
- Nov 13, 2023