---
license: apache-2.0
base_model: albert-base-v2
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: ALBERT_trainer_irony
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# ALBERT_trainer_irony

This model is a fine-tuned version of [albert-base-v2](https://huggingface.co./albert-base-v2) on the irony dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6538
- Accuracy: 0.6327

## 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: 20
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 7

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 144  | 0.7213          | 0.4901   |
| No log        | 2.0   | 288  | 0.6935          | 0.5644   |
| No log        | 3.0   | 432  | 0.6834          | 0.5906   |
| 0.6892        | 4.0   | 576  | 0.6651          | 0.6031   |
| 0.6892        | 5.0   | 720  | 0.6731          | 0.6063   |
| 0.6892        | 6.0   | 864  | 0.6892          | 0.5958   |
| 0.6185        | 7.0   | 1008 | 0.6750          | 0.6188   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2