stanfordnlp/imdb
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How to use muhtasham/tiny-mlm-tweet-target-imdb with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="muhtasham/tiny-mlm-tweet-target-imdb") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("muhtasham/tiny-mlm-tweet-target-imdb")
model = AutoModelForSequenceClassification.from_pretrained("muhtasham/tiny-mlm-tweet-target-imdb")This model is a fine-tuned version of muhtasham/tiny-mlm-tweet on the imdb 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 |
|---|---|---|---|---|---|
| 0.5661 | 0.64 | 500 | 0.3869 | 0.8363 | 0.9109 |
| 0.3798 | 1.28 | 1000 | 0.3730 | 0.8390 | 0.9125 |
| 0.3283 | 1.92 | 1500 | 0.2422 | 0.9018 | 0.9484 |
| 0.2926 | 2.56 | 2000 | 0.4156 | 0.8210 | 0.9017 |
| 0.2713 | 3.2 | 2500 | 0.3951 | 0.8405 | 0.9133 |
| 0.2519 | 3.84 | 3000 | 0.2170 | 0.9118 | 0.9539 |
| 0.2329 | 4.48 | 3500 | 0.4214 | 0.8357 | 0.9105 |
| 0.2074 | 5.12 | 4000 | 0.5114 | 0.8032 | 0.8909 |
| 0.1898 | 5.75 | 4500 | 0.4017 | 0.8486 | 0.9181 |