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llama-160m-boolq
Cheng98/llama-160m-boolq
llama-160m-boolq is a text classification model from Cheng98. Use it when you need a label for a piece of 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 Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- llama
- Access
- Public
- Created
- Apr 8, 2024
- Updated
- Apr 8, 2024
- SHA
- 32cd7a08
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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. -->
llama-160m-boolq
This model is a fine-tuned version of JackFram/llama-160m on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6795
- Accuracy: 0.5957
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: 5e-05
- train_batch_size: 16
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 0.99 | 73 | 0.6870 | 0.5731 |
| No log | 1.99 | 147 | 0.6825 | 0.5957 |
| No log | 3.0 | 221 | 0.6809 | 0.6012 |
| No log | 3.96 | 292 | 0.6795 | 0.5957 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu117
- Datasets 2.18.0
- Tokenizers 0.13.3
- Task
- Text Classification
- Library
- transformers
- Type
- llama
- License
- apache-2.0
- Created
- Apr 8, 2024
- Updated
- Apr 8, 2024