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Librarian Bot: Add base_model information to model (#6)
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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- emotion
metrics:
- accuracy
- f1
base_model: distilbert-base-uncased
model-index:
- name: distilbert-base-uncased-finetuned-emotion
results:
- task:
type: text-classification
name: Text Classification
dataset:
name: emotion
type: emotion
args: default
metrics:
- type: accuracy
value: 0.918
name: Accuracy
- type: f1
value: 0.9182094401352938
name: F1
- task:
type: text-classification
name: Text Classification
dataset:
name: emotion
type: emotion
config: default
split: test
metrics:
- type: accuracy
value: 0.9185
name: Accuracy
verified: true
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- type: precision
value: 0.8948630809230339
name: Precision Macro
verified: true
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- type: precision
value: 0.9185
name: Precision Micro
verified: true
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiOTM0YjhmZDVhYTlhZWQ3ZGQwOTRjNGI0NTU0OTFlZjFlMTE5ODQwY2E2ZTZhZmMxYjA5NDc0MzgxMjFkZjNmMyIsInZlcnNpb24iOjF9.n1LvyMO5EkZ5H7zkB533gP8w7FMpv8TxgaeaqiM-fAHmrMsF_-Dkc0X5tjI5_QQGU2aqXOHdThmWI1ohelJoDw
- type: precision
value: 0.9190547804558933
name: Precision Weighted
verified: true
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- type: recall
value: 0.860108882009274
name: Recall Macro
verified: true
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- type: recall
value: 0.9185
name: Recall Micro
verified: true
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- type: recall
value: 0.9185
name: Recall Weighted
verified: true
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- type: f1
value: 0.8727941247828231
name: F1 Macro
verified: true
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- type: f1
value: 0.9185
name: F1 Micro
verified: true
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- type: f1
value: 0.9177368694234422
name: F1 Weighted
verified: true
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- type: loss
value: 0.21989187598228455
name: loss
verified: true
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---
# distilbert-base-uncased-finetuned-emotion
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the emotion dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2287
- Accuracy: 0.918
- F1: 0.9182
## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.8478 | 1.0 | 250 | 0.3294 | 0.9015 | 0.8980 |
| 0.2616 | 2.0 | 500 | 0.2287 | 0.918 | 0.9182 |
### Framework versions
- Transformers 4.17.0
- Pytorch 1.10.0+cu111
- Datasets 1.18.4
- Tokenizers 0.11.6