transformers safetensors roberta text-classification single_label_classification dataset_size:2270482 generated_from_trainer en dataset:EPFL dataset:tweet dataset:sentiment dataset:classification base_model:vinai/bertweet-large base_model:finetune:vinai/bertweet-large license:apache-2.0 autotrain_compatible endpoints_compatible region:us
---
base_model: vinai/bertweet-large
datasets:
- EPFL
- tweet
- sentiment
- classification
language:
- en
library_name: transformers
license: apache-2.0
metrics:
- accuracy
- f1
- precision
- recall
tags:
- single_label_classification
- dataset_size:2270482
- generated_from_trainer
model-index:
- name: bertweet-large-sentiment-tuned
  results: []
---

# bertweet-large-sentiment-tuned

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: 0.9164
- F1: 0.9164
- Precision: 0.9164
- Recall: 0.9164

## 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 |
|:-------------:|:------:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.638         | 0.0400 | 1413  | 0.3125          | 0.8755   | 0.8754 | 0.8763    | 0.8755 |
| 0.2861        | 0.0800 | 2826  | 0.2491          | 0.8945   | 0.8945 | 0.8946    | 0.8945 |
| 0.2574        | 0.1200 | 4239  | 0.2395          | 0.9007   | 0.9007 | 0.9008    | 0.9007 |
| 0.2488        | 0.1600 | 5652  | 0.2286          | 0.906    | 0.9060 | 0.9061    | 0.906  |
| 0.2413        | 0.2000 | 7065  | 0.2291          | 0.9061   | 0.9061 | 0.9063    | 0.9061 |
| 0.2336        | 0.2400 | 8478  | 0.2243          | 0.9101   | 0.9101 | 0.9102    | 0.9101 |
| 0.2347        | 0.2800 | 9891  | 0.2276          | 0.9068   | 0.9068 | 0.9073    | 0.9068 |
| 0.2287        | 0.3200 | 11304 | 0.2298          | 0.9065   | 0.9065 | 0.9072    | 0.9065 |
| 0.2308        | 0.3600 | 12717 | 0.2236          | 0.9064   | 0.9064 | 0.9071    | 0.9064 |
| 0.2284        | 0.4000 | 14130 | 0.2155          | 0.9107   | 0.9107 | 0.9107    | 0.9107 |
| 0.2222        | 0.4400 | 15543 | 0.2191          | 0.9121   | 0.9121 | 0.9121    | 0.9121 |
| 0.2223        | 0.4801 | 16956 | 0.2148          | 0.9121   | 0.9121 | 0.9121    | 0.9121 |
| 0.2224        | 0.5201 | 18369 | 0.2197          | 0.9087   | 0.9086 | 0.9102    | 0.9087 |
| 0.2249        | 0.5601 | 19782 | 0.2117          | 0.9126   | 0.9126 | 0.9126    | 0.9126 |
| 0.2204        | 0.6001 | 21195 | 0.2138          | 0.914    | 0.9140 | 0.9142    | 0.914  |
| 0.2191        | 0.6401 | 22608 | 0.2210          | 0.9115   | 0.9115 | 0.9117    | 0.9115 |
| 0.216         | 0.6801 | 24021 | 0.2160          | 0.9127   | 0.9127 | 0.9128    | 0.9127 |
| 0.2159        | 0.7201 | 25434 | 0.2158          | 0.9125   | 0.9125 | 0.9125    | 0.9125 |
| 0.2191        | 0.7601 | 26847 | 0.2125          | 0.9121   | 0.9121 | 0.9123    | 0.9121 |
| 0.2167        | 0.8001 | 28260 | 0.2125          | 0.9146   | 0.9146 | 0.9146    | 0.9146 |
| 0.2159        | 0.8401 | 29673 | 0.2090          | 0.9136   | 0.9136 | 0.9137    | 0.9136 |
| 0.216         | 0.8801 | 31086 | 0.2116          | 0.9139   | 0.9139 | 0.9140    | 0.9139 |
| 0.2174        | 0.9201 | 32499 | 0.2087          | 0.9134   | 0.9134 | 0.9135    | 0.9134 |
| 0.2129        | 0.9601 | 33912 | 0.2094          | 0.9145   | 0.9145 | 0.9147    | 0.9145 |
| 0.2115        | 1.0001 | 35325 | 0.2093          | 0.9133   | 0.9133 | 0.9134    | 0.9133 |
| 0.1948        | 1.0401 | 36738 | 0.2112          | 0.9158   | 0.9158 | 0.9159    | 0.9158 |
| 0.1945        | 1.0801 | 38151 | 0.2098          | 0.9134   | 0.9134 | 0.9134    | 0.9134 |
| 0.1926        | 1.1201 | 39564 | 0.2257          | 0.9136   | 0.9136 | 0.9140    | 0.9136 |
| 0.1949        | 1.1601 | 40977 | 0.2138          | 0.9144   | 0.9144 | 0.9144    | 0.9144 |
| 0.197         | 1.2001 | 42390 | 0.2127          | 0.9152   | 0.9152 | 0.9154    | 0.9152 |
| 0.1934        | 1.2401 | 43803 | 0.2136          | 0.913    | 0.9130 | 0.9130    | 0.913  |
| 0.1927        | 1.2801 | 45216 | 0.2143          | 0.914    | 0.9140 | 0.9141    | 0.914  |
| 0.1943        | 1.3201 | 46629 | 0.2145          | 0.9141   | 0.9141 | 0.9141    | 0.9141 |
| 0.1927        | 1.3602 | 48042 | 0.2135          | 0.9146   | 0.9146 | 0.9146    | 0.9146 |
| 0.1962        | 1.4002 | 49455 | 0.2120          | 0.9138   | 0.9138 | 0.9138    | 0.9138 |
| 0.1943        | 1.4402 | 50868 | 0.2128          | 0.9161   | 0.9161 | 0.9161    | 0.9161 |
| 0.1913        | 1.4802 | 52281 | 0.2150          | 0.9157   | 0.9157 | 0.9157    | 0.9157 |
| 0.1926        | 1.5202 | 53694 | 0.2094          | 0.9158   | 0.9158 | 0.9161    | 0.9158 |
| 0.1944        | 1.5602 | 55107 | 0.2102          | 0.9155   | 0.9155 | 0.9156    | 0.9155 |
| 0.1926        | 1.6002 | 56520 | 0.2113          | 0.9162   | 0.9162 | 0.9162    | 0.9162 |
| 0.1893        | 1.6402 | 57933 | 0.2138          | 0.9142   | 0.9142 | 0.9142    | 0.9142 |
| 0.1925        | 1.6802 | 59346 | 0.2113          | 0.9167   | 0.9167 | 0.9167    | 0.9167 |
| 0.1913        | 1.7202 | 60759 | 0.2087          | 0.9159   | 0.9159 | 0.9159    | 0.9159 |
| 0.1899        | 1.7602 | 62172 | 0.2122          | 0.9164   | 0.9164 | 0.9164    | 0.9164 |
| 0.193         | 1.8002 | 63585 | 0.2099          | 0.9168   | 0.9168 | 0.9169    | 0.9168 |
| 0.19          | 1.8402 | 64998 | 0.2085          | 0.9155   | 0.9155 | 0.9155    | 0.9155 |
| 0.1888        | 1.8802 | 66411 | 0.2077          | 0.9166   | 0.9166 | 0.9166    | 0.9166 |
| 0.1899        | 1.9202 | 67824 | 0.2075          | 0.9167   | 0.9167 | 0.9167    | 0.9167 |
| 0.1887        | 1.9602 | 69237 | 0.2088          | 0.9164   | 0.9164 | 0.9164    | 0.9164 |


### Framework versions

- Transformers 4.47.0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
