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---
license: apache-2.0
base_model: distilbert-base-cased
tags:
- simplification
- generated_from_trainer
metrics:
- precision
- recall
- f1
model-index:
- name: finetuned_model_sentiment_analysis_yelp
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. -->
# finetuned_model_sentiment_analysis_yelp
This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8946
- Precision: 0.6385
- Recall: 0.6403
- F1: 0.6393
## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|
| 0.869 | 1.0 | 3657 | 0.8714 | 0.6245 | 0.6215 | 0.6221 |
| 0.7681 | 2.0 | 7314 | 0.8618 | 0.6302 | 0.6380 | 0.6299 |
| 0.6283 | 3.0 | 10971 | 0.8946 | 0.6385 | 0.6403 | 0.6393 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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