tinybert emotion This model is a fine tuned version of bert tiny on the emotion balanced dataset. It achieves the following results on the evaluation set: Loss: 0.1809 Accuracy: 0.9354 Model description TinyBERT is 7.5 times smaller and 9.4 times faster on inference compared to its teacher BERT model (while DistilBERT is 40% smaller and 1.6 times faster than BERT). The model has been trained on 89 754 examples split into train, validation and test. Each label was perfectly balanced in each split. Intended uses & limitations This model is not as accurate as the distilbert emotion balanced one because the focus was on speed, which can lead to misinterpretation of complex sentences. Despite this, its performance is quite good and should be more than sufficient for most use cases. Usage: This model faces challenges in accurately categorizing negative sentences, as well as those containing elements of sarcasm or irony. These limitations are largely attributable to TinyBERT's constrained capabilities in semantic understanding. Although the model is generally proficient in emotion detection tasks, it may lack the nuance necessary for interpreting complex emotional nuances. Training and ev…
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