README.md

metadata

license: mit
tags:
  - generated_from_trainer
datasets:
  - tweet_eval
metrics:
  - accuracy
  - f1
model-index:
  - name: tweet_eval-sentiment-finetuned
    results:
      - task:
          name: Sentiment Analysis
          type: sentiment-analysis
        dataset:
          name: tweeteval
          type: tweeteval
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.7099
          - name: f1
            type: f1
            value: 0.7097

tweet_eval-sentiment-finetuned

This model is a fine-tuned version of microsoft/deberta-v3-small on the Tweet_Eval dataset. It achieves the following results on the evaluation set:

• Loss: 0.6532
• Accuracy: 0.744
• F1: 0.7437

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: 3e-05
• train_batch_size: 128
• eval_batch_size: 256
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 4
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.7491	1.0	357	0.6089	0.7345	0.7314
0.5516	2.0	714	0.5958	0.751	0.7516
0.4618	3.0	1071	0.6131	0.748	0.7487
0.4066	4.0	1428	0.6532	0.744	0.7437

Framework versions

• Transformers 4.18.0
• Pytorch 1.9.1
• Datasets 2.1.0
• Tokenizers 0.12.1