metadata

license: mit
base_model: xlnet-base-cased
tags:
  - generated_from_trainer
datasets:
  - tweet_sentiment_multilingual
metrics:
  - accuracy
model-index:
  - name: xlnet-finetuned-socialmediatweet
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: tweet_sentiment_multilingual
          type: tweet_sentiment_multilingual
          config: english
          split: validation
          args: english
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.7129629850387573

xlnet-finetuned-socialmediatweet

This model is a fine-tuned version of xlnet-base-cased on the tweet_sentiment_multilingual dataset. It achieves the following results on the evaluation set:

Loss: 2.6923
Accuracy: 0.7130

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: 32
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.0161	1.0	58	2.4538	0.6821
0.0416	2.0	116	2.3751	0.6821
0.0294	3.0	174	2.4929	0.7068
0.031	4.0	232	2.5655	0.7037
0.0422	5.0	290	3.0881	0.6605
0.0751	6.0	348	2.6787	0.6883
0.0264	7.0	406	2.5283	0.7006
0.0123	8.0	464	2.5634	0.7006
0.0277	9.0	522	2.7127	0.6852
0.0448	10.0	580	2.6113	0.6759
0.0261	11.0	638	2.6640	0.6759
0.0111	12.0	696	2.6089	0.6914
0.0239	13.0	754	2.5785	0.6975
0.0255	14.0	812	2.6923	0.7130
0.0242	15.0	870	2.4704	0.7068
0.0131	16.0	928	2.6724	0.6667
0.0059	17.0	986	2.5554	0.7068
0.0066	18.0	1044	2.6696	0.6698
0.001	19.0	1102	2.5653	0.6883
0.0026	20.0	1160	2.5846	0.6883

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu118
Datasets 2.15.0
Tokenizers 0.15.0