Instructions to use adith-ds/results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use adith-ds/results with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="adith-ds/results")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("adith-ds/results") model = AutoModelForSequenceClassification.from_pretrained("adith-ds/results") - Notebooks
- Google Colab
- Kaggle
adith-ds/emotion-classifier-v2
Browse files- README.md +14 -14
- model.safetensors +1 -1
README.md
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Macro F1: 0.
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- Macro Precision: 0.
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- Macro Recall: 0.
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- Macro Support: None
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | Macro F1 | Macro Precision | Macro Recall | Macro Support |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------------:|:------------:|:-------------:|
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| No log | 1.0 | 86 | 0.
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### Framework versions
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3095
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- Macro F1: 0.8317
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- Macro Precision: 0.8609
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- Macro Recall: 0.8061
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- Macro Support: None
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | Macro F1 | Macro Precision | Macro Recall | Macro Support |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------------:|:------------:|:-------------:|
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| No log | 1.0 | 86 | 0.5550 | 0.1427 | 0.1109 | 0.2 | None |
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| 0.6112 | 2.0 | 172 | 0.4244 | 0.5106 | 0.7966 | 0.4864 | None |
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| 0.4482 | 3.0 | 258 | 0.3317 | 0.7370 | 0.7756 | 0.7129 | None |
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| 0.3083 | 4.0 | 344 | 0.3029 | 0.7749 | 0.8252 | 0.7414 | None |
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| 0.2015 | 5.0 | 430 | 0.2997 | 0.7893 | 0.8241 | 0.7742 | None |
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| 0.1252 | 6.0 | 516 | 0.2980 | 0.8110 | 0.8430 | 0.7882 | None |
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| 0.0736 | 7.0 | 602 | 0.3023 | 0.8148 | 0.8565 | 0.7811 | None |
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| 0.0736 | 8.0 | 688 | 0.3091 | 0.8279 | 0.8448 | 0.8135 | None |
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| 0.0384 | 9.0 | 774 | 0.3087 | 0.8313 | 0.8613 | 0.8062 | None |
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| 0.0216 | 10.0 | 860 | 0.3095 | 0.8317 | 0.8609 | 0.8061 | None |
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### Framework versions
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model.safetensors
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