dair-ai/emotion
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How to use hamzasidat/BertResults2 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="hamzasidat/BertResults2") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("hamzasidat/BertResults2")
model = AutoModelForSequenceClassification.from_pretrained("hamzasidat/BertResults2", device_map="auto")This model is a fine-tuned version of bert-base-uncased on the emotion dataset. It achieves the following results on the evaluation set:
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The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.2236 | 1.0 | 1000 | 0.1929 | 0.924 |
| 0.1179 | 2.0 | 2000 | 0.1487 | 0.94 |
Base model
google-bert/bert-base-uncased