---
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-STEP7_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-STEP7_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: 0.0002
- Accuracy: 1.0
- F1: 1.0
- Precision: 1.0
- Recall: 1.0
- Accuracy Label  gd622:null: 0.0
- Accuracy Label Gd622:null: 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 20

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy | F1  | Precision | Recall | Accuracy Label  gd622:null | Accuracy Label Gd622:null | Accuracy Label Gd622:yes |
|:-------------:|:-------:|:----:|:---------------:|:--------:|:---:|:---------:|:------:|:--------------------------:|:-------------------------:|:------------------------:|
| 0.2172        | 2.0833  | 100  | 0.1748          | 1.0      | 1.0 | 1.0       | 1.0    | 0.0                        | 1.0                       | 1.0                      |
| 0.0224        | 4.1667  | 200  | 0.0035          | 1.0      | 1.0 | 1.0       | 1.0    | 0.0                        | 1.0                       | 1.0                      |
| 0.0015        | 6.25    | 300  | 0.0014          | 1.0      | 1.0 | 1.0       | 1.0    | 0.0                        | 1.0                       | 1.0                      |
| 0.0098        | 8.3333  | 400  | 0.0007          | 1.0      | 1.0 | 1.0       | 1.0    | 0.0                        | 1.0                       | 1.0                      |
| 0.0094        | 10.4167 | 500  | 0.0004          | 1.0      | 1.0 | 1.0       | 1.0    | 0.0                        | 1.0                       | 1.0                      |
| 0.0003        | 12.5    | 600  | 0.0003          | 1.0      | 1.0 | 1.0       | 1.0    | 0.0                        | 1.0                       | 1.0                      |
| 0.0002        | 14.5833 | 700  | 0.0002          | 1.0      | 1.0 | 1.0       | 1.0    | 0.0                        | 1.0                       | 1.0                      |
| 0.0002        | 16.6667 | 800  | 0.0002          | 1.0      | 1.0 | 1.0       | 1.0    | 0.0                        | 1.0                       | 1.0                      |
| 0.0002        | 18.75   | 900  | 0.0002          | 1.0      | 1.0 | 1.0       | 1.0    | 0.0                        | 1.0                       | 1.0                      |


### Framework versions

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