---
base_model: kghanlon/distilbert-base-uncased-finetuned-MP-unannotated-half-frozen-v1
tags:
- generated_from_trainer
metrics:
- accuracy
- recall
- f1
model-index:
- name: distilbert-base-uncased-finetuned-MP-unannotated-half-frozen-v1-FULL_CLASSES-v1_un_frozen
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# distilbert-base-uncased-finetuned-MP-unannotated-half-frozen-v1-FULL_CLASSES-v1_un_frozen

This model is a fine-tuned version of [kghanlon/distilbert-base-uncased-finetuned-MP-unannotated-half-frozen-v1](https://huggingface.co/kghanlon/distilbert-base-uncased-finetuned-MP-unannotated-half-frozen-v1) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2635
- Accuracy: 0.5909
- Recall: 0.5909
- F1: 0.5861

## 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: 8
- 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 | Recall | F1     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:------:|
| 1.7051        | 1.0   | 15490 | 1.6329          | 0.5557   | 0.5557 | 0.5381 |
| 1.3579        | 2.0   | 30980 | 1.5647          | 0.5771   | 0.5771 | 0.5650 |
| 1.0119        | 3.0   | 46470 | 1.6397          | 0.5900   | 0.5900 | 0.5821 |
| 0.5922        | 4.0   | 61960 | 1.9336          | 0.5922   | 0.5922 | 0.5855 |
| 0.3721        | 5.0   | 77450 | 2.2635          | 0.5909   | 0.5909 | 0.5861 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0