---
base_model: allenai/scibert_scivocab_uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: test_TwoWayLoss_25K_bs64_P4_N1
  results: []
---

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# test_TwoWayLoss_25K_bs64_P4_N1

This model is a fine-tuned version of [allenai/scibert_scivocab_uncased](https://huggingface.co/allenai/scibert_scivocab_uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 8.8668
- Accuracy: 0.5430
- Precision: 0.0114
- Recall: 0.5359
- F1: 0.0224
- Hamming: 0.4570

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-------:|
| 8.9097        | 0.0   | 5    | 8.8974          | 0.5287   | 0.0107    | 0.5189 | 0.0210 | 0.4713  |
| 8.1387        | 0.0   | 10   | 8.8668          | 0.5430   | 0.0114    | 0.5359 | 0.0224 | 0.4570  |


### Framework versions

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