---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: test_twowayloss_implementation
  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. -->

# test_twowayloss_implementation

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 8.9001
- Accuracy: 0.5659
- Precision: 0.0114
- Recall: 0.5082
- F1: 0.0223
- Hamming: 0.4341

## 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: 2e-05
- train_batch_size: 8
- 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_ratio: 0.1
- training_steps: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     | Hamming |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-------:|
| 8.8818        | 0.0   | 5    | 8.9210          | 0.5632   | 0.0110    | 0.4947 | 0.0216 | 0.4368  |
| 8.124         | 0.0   | 10   | 8.9001          | 0.5659   | 0.0114    | 0.5082 | 0.0223 | 0.4341  |


### Framework versions

- Transformers 4.35.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.7.1
- Tokenizers 0.14.1