cardiffnlp/tweet_eval
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How to use muhtasham/small-mlm-imdb-target-tweet with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="muhtasham/small-mlm-imdb-target-tweet") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("muhtasham/small-mlm-imdb-target-tweet")
model = AutoModelForSequenceClassification.from_pretrained("muhtasham/small-mlm-imdb-target-tweet", device_map="auto")This model is a fine-tuned version of muhtasham/small-mlm-imdb on the tweet_eval 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 | F1 |
|---|---|---|---|---|---|
| 0.5821 | 4.9 | 500 | 0.8006 | 0.7540 | 0.7514 |
| 0.1013 | 9.8 | 1000 | 1.1662 | 0.7567 | 0.7562 |
| 0.0236 | 14.71 | 1500 | 1.5152 | 0.7540 | 0.7518 |
| 0.0125 | 19.61 | 2000 | 1.6963 | 0.7620 | 0.7581 |
| 0.0068 | 24.51 | 2500 | 1.9273 | 0.7380 | 0.7383 |
| 0.0042 | 29.41 | 3000 | 2.0042 | 0.7487 | 0.7500 |
| 0.0041 | 34.31 | 3500 | 2.2131 | 0.7406 | 0.7432 |