---
license: apache-2.0
base_model: albert/albert-base-v2
tags:
- trl
- sft
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: classify-ISIN-STEP8_binary
  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. -->

# classify-ISIN-STEP8_binary

This model is a fine-tuned version of [albert/albert-base-v2](https://huggingface.co/albert/albert-base-v2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0001
- Accuracy: 1.0
- F1: 1.0
- Precision: 1.0
- Recall: 1.0
- Accuracy Label Gd622:no: 1.0
- Accuracy Label Gd622:yes: 1.0

## 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
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     | Precision | Recall | Accuracy Label Gd622:no | Accuracy Label Gd622:yes |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:-----------------------:|:------------------------:|
| 0.0992        | 0.1610 | 100  | 0.0070          | 0.9987   | 0.9987 | 0.9987    | 0.9987 | 0.9982                  | 1.0                      |
| 0.0082        | 0.3221 | 200  | 0.0002          | 1.0      | 1.0    | 1.0       | 1.0    | 1.0                     | 1.0                      |
| 0.0002        | 0.4831 | 300  | 0.0001          | 1.0      | 1.0    | 1.0       | 1.0    | 1.0                     | 1.0                      |
| 0.0001        | 0.6441 | 400  | 0.0001          | 1.0      | 1.0    | 1.0       | 1.0    | 1.0                     | 1.0                      |
| 0.0001        | 0.8052 | 500  | 0.0001          | 1.0      | 1.0    | 1.0       | 1.0    | 1.0                     | 1.0                      |
| 0.0052        | 0.9662 | 600  | 0.0001          | 1.0      | 1.0    | 1.0       | 1.0    | 1.0                     | 1.0                      |


### Framework versions

- Transformers 4.43.3
- Pytorch 2.4.0
- Datasets 2.20.0
- Tokenizers 0.19.1