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End of training
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metadata
license: cc-by-sa-4.0
base_model: aiknowyou/it-emotion-analyzer
tags:
  - generated_from_trainer
metrics:
  - f1
  - accuracy
model-index:
  - name: it-emotion-analyzer_finetuned_pro_multilbel_emit
    results: []

it-emotion-analyzer_finetuned_pro_multilbel_emit

This model is a fine-tuned version of aiknowyou/it-emotion-analyzer on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2714
  • F1: 0.4804
  • Roc Auc: 0.6939
  • Accuracy: 0.3110

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: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss F1 Roc Auc Accuracy
0.2712 1.0 1037 0.2740 0.3755 0.6250 0.2680
0.2238 2.0 2074 0.2703 0.4161 0.6504 0.2749
0.1743 3.0 3111 0.2714 0.4804 0.6939 0.3110
0.143 4.0 4148 0.2838 0.4632 0.6811 0.2887
0.1089 5.0 5185 0.2971 0.4756 0.6897 0.3041
0.0874 6.0 6222 0.3242 0.4718 0.6965 0.2887
0.0726 7.0 7259 0.3414 0.4798 0.7003 0.3076
0.0565 8.0 8296 0.3538 0.4690 0.6897 0.2973
0.0501 9.0 9333 0.3712 0.4696 0.6959 0.2938
0.0426 10.0 10370 0.3692 0.4702 0.6922 0.2904

Framework versions

  • Transformers 4.40.1
  • Pytorch 2.3.0+cu118
  • Datasets 2.19.0
  • Tokenizers 0.19.1