elyadenysova
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Irony_Albert

Text Classification

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Irony_Albert

This model is a fine-tuned version of albert-base-v2 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.6721
Accuracy: 0.5829

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: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	179	0.6846	0.5686
No log	2.0	358	0.6878	0.5581
0.6943	3.0	537	0.6786	0.5853

Framework versions

Transformers 4.38.2
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2

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Safetensors

Model size

11.7M params

Tensor type

F32

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Text Classification

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Base model

albert/albert-base-v2

Finetuned

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Evaluation results

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