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twitter-xlm-roberta-base-sentiment

Text Classification
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xlm-roberta
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Anthony Ndung'u commited on
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End of training

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  1. README.md +13 -13
  2. model.safetensors +1 -1
  3. runs/Nov08_14-01-25_d7d94f1bc17a/events.out.tfevents.1699452214.d7d94f1bc17a.298.0 +2 -2
  4. runs/Nov08_14-01-25_d7d94f1bc17a/events.out.tfevents.1699453527.d7d94f1bc17a.298.1 +3 -0
README.md CHANGED
@@ -14,8 +14,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [cardiffnlp/twitter-xlm-roberta-base-sentiment](https://huggingface.co/cardiffnlp/twitter-xlm-roberta-base-sentiment) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.6716
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- - Rmse: 0.7078
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  ## Model description
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@@ -46,21 +46,21 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Rmse |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|
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- | 0.7639 | 1.0 | 500 | 0.7273 | 0.7639 |
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- | 0.6884 | 2.0 | 1000 | 0.6900 | 0.7580 |
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- | 0.6088 | 3.0 | 1500 | 0.6716 | 0.7078 |
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- | 0.4964 | 4.0 | 2000 | 0.6728 | 0.6826 |
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- | 0.3749 | 5.0 | 2500 | 0.8286 | 0.6753 |
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- | 0.2813 | 6.0 | 3000 | 0.9432 | 0.6968 |
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- | 0.2173 | 7.0 | 3500 | 1.2781 | 0.7235 |
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- | 0.1764 | 8.0 | 4000 | 1.3567 | 0.7221 |
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- | 0.122 | 9.0 | 4500 | 1.5207 | 0.7004 |
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- | 0.0946 | 10.0 | 5000 | 1.5687 | 0.6996 |
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  ### Framework versions
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- - Transformers 4.34.1
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  - Pytorch 2.1.0+cu118
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  - Datasets 2.14.6
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  - Tokenizers 0.14.1
 
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  This model is a fine-tuned version of [cardiffnlp/twitter-xlm-roberta-base-sentiment](https://huggingface.co/cardiffnlp/twitter-xlm-roberta-base-sentiment) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.6295
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+ - Rmse: 0.7173
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Rmse |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|
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+ | 0.7384 | 1.0 | 500 | 0.7162 | 0.7593 |
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+ | 0.6322 | 2.0 | 1000 | 0.6433 | 0.7228 |
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+ | 0.541 | 3.0 | 1500 | 0.6295 | 0.7173 |
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+ | 0.4118 | 4.0 | 2000 | 0.7930 | 0.6804 |
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+ | 0.2949 | 5.0 | 2500 | 0.8727 | 0.6756 |
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+ | 0.2109 | 6.0 | 3000 | 1.2173 | 0.7211 |
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+ | 0.1558 | 7.0 | 3500 | 1.5233 | 0.7249 |
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+ | 0.1077 | 8.0 | 4000 | 1.6957 | 0.7162 |
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+ | 0.0767 | 9.0 | 4500 | 1.8504 | 0.6982 |
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+ | 0.0534 | 10.0 | 5000 | 1.9203 | 0.7068 |
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  ### Framework versions
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+ - Transformers 4.35.0
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  - Pytorch 2.1.0+cu118
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  - Datasets 2.14.6
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  - Tokenizers 0.14.1
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