LLM / README.md
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---
license: apache-2.0
base_model: bert-large-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: LLM
results: []
---
<!-- 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. -->
# LLM
This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co./bert-large-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7030
- Accuracy: 0.15
## 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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 12 | 1.6756 | 0.1 |
| No log | 2.0 | 24 | 1.6728 | 0.15 |
| No log | 3.0 | 36 | 1.6773 | 0.2 |
| No log | 4.0 | 48 | 1.6952 | 0.2 |
| No log | 5.0 | 60 | 1.7030 | 0.15 |
### Framework versions
- Transformers 4.32.1
- Pytorch 1.13.1
- Datasets 2.14.4
- Tokenizers 0.13.3