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---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
datasets:
- financial_phrasebank
metrics:
- accuracy
model-index:
- name: distilbert-finance
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: financial_phrasebank
type: financial_phrasebank
config: sentences_50agree
split: train
args: sentences_50agree
metrics:
- name: Accuracy
type: accuracy
value: 0.7045454545454546
---
<!-- 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-finance
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the financial_phrasebank dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7474
- Accuracy: 0.7045
## 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: 0.0002
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6755 | 0.33 | 20 | 1.4948 | 0.3709 |
| 0.4585 | 0.66 | 40 | 0.9705 | 0.6147 |
| 0.4267 | 0.98 | 60 | 1.2383 | 0.6012 |
| 0.3298 | 1.31 | 80 | 1.0040 | 0.5764 |
| 0.2955 | 1.64 | 100 | 1.4078 | 0.4845 |
| 0.2521 | 1.97 | 120 | 1.2183 | 0.5702 |
| 0.1614 | 2.3 | 140 | 1.4761 | 0.6570 |
| 0.1842 | 2.62 | 160 | 1.8172 | 0.6002 |
| 0.2124 | 2.95 | 180 | 0.9596 | 0.7211 |
| 0.1016 | 3.28 | 200 | 1.3150 | 0.6952 |
| 0.0949 | 3.61 | 220 | 1.5779 | 0.6498 |
| 0.102 | 3.93 | 240 | 1.9178 | 0.5775 |
| 0.0542 | 4.26 | 260 | 2.0914 | 0.6074 |
| 0.059 | 4.59 | 280 | 1.7965 | 0.6560 |
| 0.0578 | 4.92 | 300 | 2.0358 | 0.5279 |
| 0.0335 | 5.25 | 320 | 1.5614 | 0.6829 |
| 0.0414 | 5.57 | 340 | 1.8126 | 0.6405 |
| 0.0263 | 5.9 | 360 | 1.4405 | 0.6798 |
| 0.0257 | 6.23 | 380 | 1.0230 | 0.7417 |
| 0.0123 | 6.56 | 400 | 1.9126 | 0.6818 |
| 0.0218 | 6.89 | 420 | 1.8622 | 0.6860 |
| 0.0063 | 7.21 | 440 | 2.0173 | 0.6705 |
| 0.014 | 7.54 | 460 | 1.9129 | 0.6870 |
| 0.0037 | 7.87 | 480 | 1.7622 | 0.7035 |
| 0.0155 | 8.2 | 500 | 1.7379 | 0.7004 |
| 0.0087 | 8.52 | 520 | 1.7150 | 0.6994 |
| 0.0055 | 8.85 | 540 | 1.7286 | 0.7025 |
| 0.0051 | 9.18 | 560 | 1.7418 | 0.7014 |
| 0.0049 | 9.51 | 580 | 1.7468 | 0.7035 |
| 0.0056 | 9.84 | 600 | 1.7474 | 0.7045 |
### Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3
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