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README.md
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# `vocabtrimmer/xlm-roberta-base-trimmed-en-30000-tweet-sentiment-en`
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This model is a fine-tuned version of [/home/asahiushio/Projects/lm-vocab-trimmer/ckpts/xlm-roberta-base-trimmed-en-30000](https://huggingface.co//home/asahiushio/Projects/lm-vocab-trimmer/ckpts/xlm-roberta-base-trimmed-en-30000) on the
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[cardiffnlp/tweet_sentiment_multilingual](https://huggingface.co/datasets/cardiffnlp/tweet_sentiment_multilingual) (english).
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Following metrics are computed on the `test` split of
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[cardiffnlp/tweet_sentiment_multilingual](https://huggingface.co/datasets/cardiffnlp/tweet_sentiment_multilingual)(english).
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| | eval_f1_micro | eval_recall_micro | eval_precision_micro | eval_f1_macro | eval_recall_macro | eval_precision_macro | eval_accuracy |
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|---:|----------------:|--------------------:|-----------------------:|----------------:|--------------------:|-----------------------:|----------------:|
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| 0 | 66.55 | 66.55 | 66.55 | 66.02 | 66.55 | 66.71 | 66.55 |
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Check the result file [here](https://huggingface.co/vocabtrimmer/xlm-roberta-base-trimmed-en-30000-tweet-sentiment-en/raw/main/eval.json).
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eval.json
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{"eval_loss": 1.1621949672698975, "eval_f1_micro": 0.6655172413793103, "eval_recall_micro": 0.6655172413793103, "eval_precision_micro": 0.6655172413793103, "eval_f1_macro": 0.6601504234199874, "eval_recall_macro": 0.6655172413793103, "eval_precision_macro": 0.6671029553352367, "eval_accuracy": 0.6655172413793103, "eval_runtime": 2.3385, "eval_samples_per_second": 372.03, "eval_steps_per_second": 46.611}
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