---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: bert-base-uncased-rte-ia3-epochs-10-lr-0.005
  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. -->

# bert-base-uncased-rte-ia3-epochs-10-lr-0.005

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co./bert-base-uncased) on the glue dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6986
- Accuracy: 0.7

## 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: 0.005
- train_batch_size: 32
- eval_batch_size: 32
- seed: 28
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.06
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 75   | 0.6797          | 0.58     |
| No log        | 2.0   | 150  | 0.6631          | 0.61     |
| No log        | 3.0   | 225  | 0.6239          | 0.62     |
| No log        | 4.0   | 300  | 0.5983          | 0.63     |
| No log        | 5.0   | 375  | 0.6250          | 0.68     |
| No log        | 6.0   | 450  | 0.6487          | 0.67     |
| 0.6417        | 7.0   | 525  | 0.6473          | 0.64     |
| 0.6417        | 8.0   | 600  | 0.6558          | 0.68     |
| 0.6417        | 9.0   | 675  | 0.6865          | 0.69     |
| 0.6417        | 10.0  | 750  | 0.6986          | 0.7      |


### Framework versions

- Transformers 4.32.0.dev0
- Pytorch 2.0.1
- Datasets 2.14.4
- Tokenizers 0.13.3