Pannathad/xlm-roberta-base-th-product-review-sentiment-analysis

<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->

output2

This model is a fine-tuned version of xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:

• —Loss: 1.0553
• —Accuracy: 0.7264
• —F1: 0.7307

Model description

  from transformers import pipeline
 
  model = pipeline(model="Pannathad/xlm-roberta-base-th-product-review-sentiment-analysis")
  result = model(["มีการกันกระแทกอย่างดี", "มีการห่อบับเบิ้ลอย่างหนา","มาส่งไว","แต่ราคาแพงมาก"])
  # result
  [
    {'label': 'Quality', 'score': 0.8555123209953308},
    {'label': 'Packaging', 'score': 0.9143754243850708},
    {'label': 'DeliveryTime', 'score': 0.9672013521194458},
    {'label': 'NEG-Price', 'score': 0.6597796082496643}
  ]

 

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
• —trainbatchsize: 64
• —evalbatchsize: 128
• —seed: 42
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: linear
• —num_epochs: 25
• —mixedprecisiontraining: Native AMP

Training results

Framework versions

• —Transformers 4.41.2
• —Pytorch 2.3.0+cu121
• —Datasets 2.20.0
• —Tokenizers 0.19.1