model update
Browse files
README.md
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@@ -5,7 +5,7 @@ metrics:
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- f1
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- accuracy
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model-index:
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- name: roberta-base-tweet-topic-single-all
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results:
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- task:
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type: text-classification
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- text: "Love to take night time bike rides at the jersey shore. Seaside Heights boardwalk. Beautiful weather. Wishing everyone a safe Labor Day weekend in the US."
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example_title: "Example 2"
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---
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# roberta-base-tweet-topic-single-all
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This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the [tweet_topic_single](https://huggingface.co/datasets/cardiffnlp/tweet_topic_single). This model is fine-tuned on `train_all` split and validated on `test_2021` split of tweet_topic.
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Fine-tuning script can be found [here](https://huggingface.co/datasets/cardiffnlp/tweet_topic_single/blob/main/lm_finetuning.py). It achieves the following results on the test_2021 set:
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@@ -47,7 +47,7 @@ Fine-tuning script can be found [here](https://huggingface.co/datasets/cardiffnl
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```python
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from transformers import pipeline
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pipe = pipeline("text-classification", "roberta-base-tweet-topic-single-all")
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topic = pipe("Love to take night time bike rides at the jersey shore. Seaside Heights boardwalk. Beautiful weather. Wishing everyone a safe Labor Day weekend in the US.")
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print(topic)
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```
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- f1
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- accuracy
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model-index:
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- name: cardiffnlp/roberta-base-tweet-topic-single-all
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results:
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- task:
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type: text-classification
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- text: "Love to take night time bike rides at the jersey shore. Seaside Heights boardwalk. Beautiful weather. Wishing everyone a safe Labor Day weekend in the US."
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example_title: "Example 2"
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---
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+
# cardiffnlp/roberta-base-tweet-topic-single-all
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This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the [tweet_topic_single](https://huggingface.co/datasets/cardiffnlp/tweet_topic_single). This model is fine-tuned on `train_all` split and validated on `test_2021` split of tweet_topic.
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Fine-tuning script can be found [here](https://huggingface.co/datasets/cardiffnlp/tweet_topic_single/blob/main/lm_finetuning.py). It achieves the following results on the test_2021 set:
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```python
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from transformers import pipeline
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pipe = pipeline("text-classification", "cardiffnlp/roberta-base-tweet-topic-single-all")
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topic = pipe("Love to take night time bike rides at the jersey shore. Seaside Heights boardwalk. Beautiful weather. Wishing everyone a safe Labor Day weekend in the US.")
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print(topic)
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```
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