metadata
license: mit
tags:
- generated_from_trainer
base_model: ibm/ColD-Fusion
model-index:
- name: roberta_emo
results: []
roberta_emo
This model is a fine-tuned version of ibm/ColD-Fusion on an unknown dataset.
Model description
More information needed
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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1.0
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.1
- Datasets 2.8.0
- Tokenizers 0.13.2
Model Recycling
Evaluation on 36 datasets using gustavecortal/roberta_emo as a base model yields average score of 78.47 in comparison to 76.22 by roberta-base.
The model is ranked 2nd among all tested models for the roberta-base architecture as of 18/01/2023 Results:
| 20_newsgroup | ag_news | amazon_reviews_multi | anli | boolq | cb | cola | copa | dbpedia | esnli | financial_phrasebank | imdb | isear | mnli | mrpc | multirc | poem_sentiment | qnli | qqp | rotten_tomatoes | rte | sst2 | sst_5bins | stsb | trec_coarse | trec_fine | tweet_ev_emoji | tweet_ev_emotion | tweet_ev_hate | tweet_ev_irony | tweet_ev_offensive | tweet_ev_sentiment | wic | wnli | wsc | yahoo_answers |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 85.8205 | 90.2333 | 66.08 | 52.1563 | 81.6208 | 89.2857 | 83.4132 | 71 | 77.5 | 90.6963 | 86.1 | 93.776 | 73.0117 | 86.8186 | 88.2353 | 64.0677 | 88.4615 | 92.8794 | 90.9523 | 91.3696 | 83.3935 | 95.7569 | 57.4661 | 91.5106 | 97.2 | 91.2 | 45.994 | 82.4771 | 52.4916 | 75.6378 | 86.6279 | 70.8727 | 68.4953 | 46.4789 | 63.4615 | 72.2667 |
For more information, see: Model Recycling