LABEL_0 LABEL_1 LABEL_2 LABEL_3
---
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: distilrubert-tiny-2nd-finetune-epru
  results: []
---

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# distilrubert-tiny-2nd-finetune-epru

This model is a fine-tuned version of [mmillet/distilrubert-tiny-cased-conversational-v1_single_finetuned_on_cedr_augmented](https://huggingface.co/mmillet/distilrubert-tiny-cased-conversational-v1_single_finetuned_on_cedr_augmented) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3546
- Accuracy: 0.9325
- F1: 0.9328
- Precision: 0.9359
- Recall: 0.9325

## 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: 0.0001
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-06
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.0686        | 1.0   | 12   | 0.2931          | 0.9141   | 0.9142 | 0.9163    | 0.9141 |
| 0.0269        | 2.0   | 24   | 0.2690          | 0.9448   | 0.9444 | 0.9449    | 0.9448 |
| 0.0282        | 3.0   | 36   | 0.3140          | 0.9141   | 0.9140 | 0.9168    | 0.9141 |
| 0.0185        | 4.0   | 48   | 0.2977          | 0.9571   | 0.9570 | 0.9576    | 0.9571 |
| 0.0103        | 5.0   | 60   | 0.3368          | 0.9264   | 0.9265 | 0.9296    | 0.9264 |
| 0.0088        | 6.0   | 72   | 0.3067          | 0.9387   | 0.9385 | 0.9389    | 0.9387 |
| 0.0152        | 7.0   | 84   | 0.3660          | 0.9264   | 0.9263 | 0.9282    | 0.9264 |
| 0.0315        | 8.0   | 96   | 0.3793          | 0.9325   | 0.9328 | 0.9359    | 0.9325 |
| 0.0258        | 9.0   | 108  | 0.3546          | 0.9325   | 0.9328 | 0.9359    | 0.9325 |


### Framework versions

- Transformers 4.19.4
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1
