---
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: distilbert-financial-time-period
  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. -->

# distilbert-financial-time-period

This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3691
- Accuracy: 0.8889
- F1: 0.8869

## 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: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 1.0   | 80   | 1.3227          | 0.6190   | 0.5528 |
| No log        | 2.0   | 160  | 0.6966          | 0.8413   | 0.8256 |
| No log        | 3.0   | 240  | 0.4750          | 0.8730   | 0.8676 |
| 0.8347        | 4.0   | 320  | 0.3859          | 0.9048   | 0.9028 |
| 0.8347        | 5.0   | 400  | 0.3788          | 0.9048   | 0.9028 |
| 0.8347        | 6.0   | 480  | 0.3691          | 0.8889   | 0.8869 |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1