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finetuning-sentiment-model-300-samples – AI Model by DaisyQue | AlphaNeural AI
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finetuning-sentiment-model-300-samples
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transformers
tensorboard
safetensors
distilbert
text-classification
generated_from_trainer
distilbert/distilbert-base-uncased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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finetuning-sentiment-model-300-samples
This model is a fine-tuned version of
distilbert-base-uncased
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.9609
Accuracy: 0.765
F1: 0.7648
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: 64
seed: 42
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 5
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1
0.2642
1.0
55
0.6175
0.783
0.7826
0.2391
2.0
110
0.6746
0.761
0.7607
0.1272
3.0
165
0.8233
0.764
0.7636
0.0772
4.0
220
0.9219
0.76
0.7594
0.0647
5.0
275
0.9609
0.765
0.7648
Framework versions
Transformers 4.46.2
Pytorch 2.5.1+cu121
Datasets 3.1.0
Tokenizers 0.20.3
