transformers safetensors roberta text-classification generated_from_trainer dataset:financial_phrasebank base_model:judy93536/distilroberta-rbm231k-ep20-op40 base_model:finetune:judy93536/distilroberta-rbm231k-ep20-op40 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: judy93536/distilroberta-rbm231k-ep20-op40
datasets:
- financial_phrasebank
license: apache-2.0
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: distilroberta-rbm231k-ep20-op40-phr2
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: financial_phrasebank
      type: financial_phrasebank
      config: sentences_allagree
      split: train
      args: sentences_allagree
    metrics:
    - type: accuracy
      value: 0.9558498896247241
      name: Accuracy
---

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# distilroberta-rbm231k-ep20-op40-phr2

This model is a fine-tuned version of [judy93536/distilroberta-rbm231k-ep20-op40](https://huggingface.co/judy93536/distilroberta-rbm231k-ep20-op40) on the financial_phrasebank dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1510
- Accuracy: 0.9558

## 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: 1.153335054745316e-06
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.4
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 114  | 1.0772          | 0.5320   |
| No log        | 2.0   | 228  | 1.0494          | 0.6159   |
| No log        | 3.0   | 342  | 0.9975          | 0.6181   |
| No log        | 4.0   | 456  | 0.9147          | 0.6181   |
| 1.0398        | 5.0   | 570  | 0.8565          | 0.6181   |
| 1.0398        | 6.0   | 684  | 0.8305          | 0.6181   |
| 1.0398        | 7.0   | 798  | 0.7759          | 0.6181   |
| 1.0398        | 8.0   | 912  | 0.7302          | 0.6490   |
| 0.8173        | 9.0   | 1026 | 0.6873          | 0.6865   |
| 0.8173        | 10.0  | 1140 | 0.6445          | 0.7174   |
| 0.8173        | 11.0  | 1254 | 0.6036          | 0.7439   |
| 0.8173        | 12.0  | 1368 | 0.5528          | 0.7550   |
| 0.8173        | 13.0  | 1482 | 0.5247          | 0.7550   |
| 0.5972        | 14.0  | 1596 | 0.4776          | 0.7572   |
| 0.5972        | 15.0  | 1710 | 0.4430          | 0.7616   |
| 0.5972        | 16.0  | 1824 | 0.3948          | 0.7704   |
| 0.5972        | 17.0  | 1938 | 0.3418          | 0.8455   |
| 0.4037        | 18.0  | 2052 | 0.2924          | 0.9029   |
| 0.4037        | 19.0  | 2166 | 0.2486          | 0.9249   |
| 0.4037        | 20.0  | 2280 | 0.2049          | 0.9360   |
| 0.4037        | 21.0  | 2394 | 0.1854          | 0.9470   |
| 0.2072        | 22.0  | 2508 | 0.1803          | 0.9470   |
| 0.2072        | 23.0  | 2622 | 0.1634          | 0.9514   |
| 0.2072        | 24.0  | 2736 | 0.1615          | 0.9536   |
| 0.2072        | 25.0  | 2850 | 0.1560          | 0.9536   |
| 0.2072        | 26.0  | 2964 | 0.1512          | 0.9558   |
| 0.1222        | 27.0  | 3078 | 0.1470          | 0.9558   |
| 0.1222        | 28.0  | 3192 | 0.1519          | 0.9536   |
| 0.1222        | 29.0  | 3306 | 0.1505          | 0.9558   |
| 0.1222        | 30.0  | 3420 | 0.1510          | 0.9558   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
