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distilbert-tweet_eval-emotion – AI Model by max-gartz | AlphaNeural AI
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max-gartz
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distilbert-tweet_eval-emotion
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transformers
onnx
safetensors
distilbert
text-classification
generated_from_trainer
distilbert/distilbert-base-uncased
quantized
apache-2.0
autotrain_compatible
endpoints_compatible
us
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distilbert-tweet_eval-emotion
This model is a fine-tuned version of
distilbert-base-uncased
on the tweet_eval dataset. It achieves the following results on the evaluation set:
Loss: 0.6404
Accuracy: 0.6529
Precision: 0.8110
Recall: 0.6529
F1: 0.6507
Auroc: 0.9184
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: 1e-05
train_batch_size: 4
eval_batch_size: 4
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
training_steps: 1000
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
Precision
Recall
F1
Auroc
0.7228
0.55
500
0.7232
0.6030
0.5625
0.6030
0.5760
0.8937
0.64
1.1
1000
0.6404
0.6529
0.8110
0.6529
0.6507
0.9184
Framework versions
Transformers 4.37.2
Pytorch 2.1.2
Datasets 2.17.0
Tokenizers 0.15.1
