--- library_name: transformers language: - en license: apache-2.0 base_model: vinai/bertweet-large tags: - single_label_classification - dataset_size:2270482 - generated_from_trainer datasets: - EPFL - tweet - sentiment - classification metrics: - accuracy - f1 - precision - recall model-index: - name: bertweet-large-sentiment-tuned-p results: [] --- # bertweet-large-sentiment-tuned-p This model is a fine-tuned version of [vinai/bertweet-large](https://huggingface.co/vinai/bertweet-large) on the EPFL CS-433 Text Classification dataset. It achieves the following results on the evaluation set: - Loss: 0.2088 - Accuracy: 0.9178 - F1: 0.9178 - Precision: 0.9178 - Recall: 0.9178 ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 4e-06 - train_batch_size: 64 - eval_batch_size: 64 - seed: 42 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 2.0 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |:-------------:|:------:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:| | 0.5966 | 0.0400 | 1413 | 0.3083 | 0.8754 | 0.8754 | 0.8756 | 0.8754 | | 0.2814 | 0.0800 | 2826 | 0.2545 | 0.8913 | 0.8913 | 0.8914 | 0.8913 | | 0.2577 | 0.1200 | 4239 | 0.2521 | 0.896 | 0.8959 | 0.8973 | 0.896 | | 0.2474 | 0.1600 | 5652 | 0.2368 | 0.9019 | 0.9019 | 0.9019 | 0.9019 | | 0.2415 | 0.2000 | 7065 | 0.2336 | 0.9023 | 0.9023 | 0.9026 | 0.9023 | | 0.2367 | 0.2400 | 8478 | 0.2423 | 0.9033 | 0.9032 | 0.9044 | 0.9033 | | 0.2338 | 0.2800 | 9891 | 0.2406 | 0.9019 | 0.9018 | 0.9036 | 0.9019 | | 0.2292 | 0.3200 | 11304 | 0.2278 | 0.9073 | 0.9073 | 0.9075 | 0.9073 | | 0.2285 | 0.3600 | 12717 | 0.2335 | 0.9083 | 0.9083 | 0.9083 | 0.9083 | | 0.224 | 0.4000 | 14130 | 0.2255 | 0.9106 | 0.9106 | 0.9108 | 0.9106 | | 0.2249 | 0.4400 | 15543 | 0.2317 | 0.91 | 0.9100 | 0.9100 | 0.91 | | 0.2227 | 0.4801 | 16956 | 0.2208 | 0.9107 | 0.9107 | 0.9113 | 0.9107 | | 0.224 | 0.5201 | 18369 | 0.2189 | 0.9108 | 0.9108 | 0.9108 | 0.9108 | | 0.2228 | 0.5601 | 19782 | 0.2177 | 0.9121 | 0.9121 | 0.9124 | 0.9121 | | 0.2216 | 0.6001 | 21195 | 0.2185 | 0.9103 | 0.9103 | 0.9103 | 0.9103 | | 0.2201 | 0.6401 | 22608 | 0.2176 | 0.9114 | 0.9114 | 0.9116 | 0.9114 | | 0.2187 | 0.6801 | 24021 | 0.2138 | 0.9126 | 0.9126 | 0.9126 | 0.9126 | | 0.2168 | 0.7201 | 25434 | 0.2135 | 0.9127 | 0.9127 | 0.9131 | 0.9127 | | 0.2185 | 0.7601 | 26847 | 0.2146 | 0.9142 | 0.9142 | 0.9142 | 0.9142 | | 0.2171 | 0.8001 | 28260 | 0.2099 | 0.9142 | 0.9142 | 0.9142 | 0.9142 | | 0.216 | 0.8401 | 29673 | 0.2103 | 0.9142 | 0.9142 | 0.9142 | 0.9142 | | 0.218 | 0.8801 | 31086 | 0.2097 | 0.9139 | 0.9139 | 0.9139 | 0.9139 | | 0.2154 | 0.9201 | 32499 | 0.2098 | 0.912 | 0.9120 | 0.9120 | 0.912 | | 0.212 | 0.9601 | 33912 | 0.2079 | 0.9147 | 0.9147 | 0.9147 | 0.9147 | | 0.2102 | 1.0001 | 35325 | 0.2105 | 0.9135 | 0.9135 | 0.9136 | 0.9135 | | 0.1938 | 1.0401 | 36738 | 0.2114 | 0.9165 | 0.9165 | 0.9166 | 0.9165 | | 0.1934 | 1.0801 | 38151 | 0.2118 | 0.9135 | 0.9135 | 0.9135 | 0.9135 | | 0.1965 | 1.1201 | 39564 | 0.2121 | 0.9142 | 0.9142 | 0.9143 | 0.9142 | | 0.1952 | 1.1601 | 40977 | 0.2156 | 0.9126 | 0.9126 | 0.9128 | 0.9126 | | 0.1911 | 1.2001 | 42390 | 0.2142 | 0.9141 | 0.9141 | 0.9143 | 0.9141 | | 0.1928 | 1.2401 | 43803 | 0.2143 | 0.9148 | 0.9148 | 0.9149 | 0.9148 | | 0.1957 | 1.2801 | 45216 | 0.2116 | 0.9133 | 0.9133 | 0.9134 | 0.9133 | | 0.1964 | 1.3201 | 46629 | 0.2108 | 0.9155 | 0.9155 | 0.9155 | 0.9155 | | 0.1916 | 1.3602 | 48042 | 0.2125 | 0.9149 | 0.9149 | 0.9149 | 0.9149 | | 0.1917 | 1.4002 | 49455 | 0.2158 | 0.9154 | 0.9154 | 0.9154 | 0.9154 | | 0.1942 | 1.4402 | 50868 | 0.2124 | 0.9143 | 0.9143 | 0.9144 | 0.9143 | | 0.1918 | 1.4802 | 52281 | 0.2075 | 0.9147 | 0.9147 | 0.9147 | 0.9147 | | 0.1931 | 1.5202 | 53694 | 0.2154 | 0.9158 | 0.9158 | 0.9158 | 0.9158 | | 0.1895 | 1.5602 | 55107 | 0.2084 | 0.916 | 0.9160 | 0.9160 | 0.916 | | 0.192 | 1.6002 | 56520 | 0.2099 | 0.917 | 0.9170 | 0.9170 | 0.917 | | 0.1948 | 1.6402 | 57933 | 0.2080 | 0.9163 | 0.9163 | 0.9163 | 0.9163 | | 0.1907 | 1.6802 | 59346 | 0.2084 | 0.9166 | 0.9166 | 0.9166 | 0.9166 | | 0.191 | 1.7202 | 60759 | 0.2094 | 0.9159 | 0.9159 | 0.9160 | 0.9159 | | 0.1878 | 1.7602 | 62172 | 0.2104 | 0.9157 | 0.9157 | 0.9157 | 0.9157 | | 0.192 | 1.8002 | 63585 | 0.2061 | 0.9179 | 0.9179 | 0.9179 | 0.9179 | | 0.1894 | 1.8402 | 64998 | 0.2092 | 0.916 | 0.9160 | 0.9160 | 0.916 | | 0.1922 | 1.8802 | 66411 | 0.2076 | 0.9165 | 0.9165 | 0.9165 | 0.9165 | | 0.1908 | 1.9202 | 67824 | 0.2071 | 0.917 | 0.9170 | 0.9170 | 0.917 | | 0.1883 | 1.9602 | 69237 | 0.2088 | 0.9178 | 0.9178 | 0.9178 | 0.9178 | ### Framework versions - Transformers 4.47.0 - Pytorch 2.5.1+cu124 - Datasets 3.2.0 - Tokenizers 0.21.0