transformers pytorch safetensors bert generated_from_trainer base_model:bert-base-uncased license:apache-2.0 endpoints_compatible region:us
---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: scenario-KD-PRE-DIV2-data-glue-rte-model-bert-base-uncased-run-1
  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. -->

# scenario-KD-PRE-DIV2-data-glue-rte-model-bert-base-uncased-run-1

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.5724
- 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6969

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 78   | 2.9400          | 0.5560   |
| No log        | 2.0   | 156  | 3.4835          | 0.5487   |
| No log        | 3.0   | 234  | 3.8960          | 0.5704   |
| No log        | 4.0   | 312  | 4.0689          | 0.5740   |
| No log        | 5.0   | 390  | 3.8711          | 0.5740   |
| No log        | 6.0   | 468  | 4.0902          | 0.5776   |
| 1.9409        | 7.0   | 546  | 4.4451          | 0.5632   |
| 1.9409        | 8.0   | 624  | 3.6043          | 0.5560   |
| 1.9409        | 9.0   | 702  | 4.2710          | 0.6101   |
| 1.9409        | 10.0  | 780  | 3.1749          | 0.5668   |
| 1.9409        | 11.0  | 858  | 3.6560          | 0.5776   |
| 1.9409        | 12.0  | 936  | 4.2378          | 0.5668   |
| 0.4992        | 13.0  | 1014 | 3.7135          | 0.5740   |
| 0.4992        | 14.0  | 1092 | 3.5724          | 0.5957   |


### Framework versions

- Transformers 4.33.3
- Pytorch 2.1.1
- Datasets 2.14.5
- Tokenizers 0.13.3
