tadiecool29/STL-afroxlmr-base-sentiment

.gitattributes

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+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

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+---
+library_name: transformers
+license: mit
+base_model: Davlan/afro-xlmr-base
+tags:
+- generated_from_trainer
+metrics:
+- f1
+model-index:
+- name: STL-afroxlmr-base-sentiment
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# STL-afroxlmr-base-sentiment
+
+This model is a fine-tuned version of [Davlan/afro-xlmr-base](https://huggingface.co/Davlan/afro-xlmr-base) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.8290
+- Sentiment Precision: 0.7115
+- Sentiment Recall: 0.7115
+- F1: 0.7113
+- Sentiment Acc: 0.7157
+
+## 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: 1e-05
+- train_batch_size: 16
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 300
+- num_epochs: 10
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Sentiment Precision | Sentiment Recall | F1     | Sentiment Acc |
+|:-------------:|:-----:|:----:|:---------------:|:-------------------:|:----------------:|:------:|:-------------:|
+| 0.7934        | 1.0   | 377  | 0.7107          | 0.7023              | 0.6982           | 0.6995 | 0.7045        |
+| 0.6659        | 2.0   | 754  | 0.6630          | 0.7249              | 0.7250           | 0.7177 | 0.7269        |
+| 0.5482        | 3.0   | 1131 | 0.6687          | 0.7192              | 0.7215           | 0.7181 | 0.7257        |
+| 0.4400        | 4.0   | 1508 | 0.7441          | 0.7226              | 0.7171           | 0.7179 | 0.7195        |
+| 0.3982        | 5.0   | 1885 | 0.7949          | 0.7109              | 0.7101           | 0.7081 | 0.7170        |
+| 0.2832        | 6.0   | 2262 | 0.8290          | 0.7115              | 0.7115           | 0.7113 | 0.7157        |
+
+
+### Framework versions
+
+- Transformers 5.16.1
+- Pytorch 2.11.0+cu128
+- Datasets 4.0.0
+- Tokenizers 0.23.1

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tokenizer.json

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tokenizer_config.json

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+  "backend": "tokenizers",
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+  "eos_token": "</s>",
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+  "mask_token": "<mask>",
+  "model_max_length": 512,
+  "pad_token": "<pad>",
+  "sep_token": "</s>",
+  "tokenizer_class": "XLMRobertaTokenizer",
+  "unk_token": "<unk>"
+}

training_args.bin

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