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---
model-index:
- name: DracoHugging/Distilbert-sentiment-analysis
results:
- task:
type: Text Classification # Required. Example: automatic-speech-recognition
name: Sentiment Analysis # Optional. Example: Speech Recognition
dataset:
type: Text-2-Text # Required. Example: common_voice. Use dataset id from https://hf.co/datasets
name: knkarthick/dialogsum # Required. A pretty name for the dataset. Example: Common Voice (French)
metrics:
- type: Validation Loss # Required. Example: wer. Use metric id from https://hf.co/metrics
value: 1.08 # Required. Example: 20.90
verified: true
---
<!-- 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-sentiment-analysis
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co./distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2745
## 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: 5e-05
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.1633 | 1.0 | 1178 | 1.1116 |
| 1.0524 | 2.0 | 2356 | 1.0836 |
| 0.9103 | 3.0 | 3534 | 1.1135 |
| 0.7676 | 4.0 | 4712 | 1.1945 |
| 0.659 | 5.0 | 5890 | 1.2745 |
### Framework versions
- Transformers 4.30.1
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3 |