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Update README.md

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@@ -84,8 +84,7 @@ At the time of submission, no measures have been taken to estimate the bias embe
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  ### Training data
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  The training corpus consists of several corpora gathered from web crawling and public corpora.
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- <details>
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- <summary>Click to expand</summary>
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  | Corpus | Size in GB |
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  |-------------------------|------------|
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  | Catalan Crawling | 13.00 |
@@ -102,7 +101,6 @@ The training corpus consists of several corpora gathered from web crawling and p
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  | Nació Digital | 0.42 |
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  | Vilaweb | 0.06 |
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  | Tweets | 0.02 |
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- </details>
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  ### Training procedure
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@@ -141,7 +139,7 @@ Here are the train/dev/test splits of each dataset:
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  This is how it compares to the teacher model when fine-tuned on the same downstream tasks:
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- | Task | NER (F1) | POS (F1) | STS-ca (Comb) | TeCla (Acc.) | TEca (Acc.) | VilaQuAD (F1/EM)| ViquiQuAD (F1/EM) | CatalanQA (F1/EM) | XQuAD-ca <sup>1</sup> (F1/EM) |
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  | ------------|:-------------:| -----:|:------|:------|:-------|:------|:----|:----|:----|
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  | RoBERTa-large-ca-v2 | 89.82 | 99.02 | 83.41 | 75.46 | 83.61 | 89.34/75.50 | 89.20/75.77 | 90.72/79.06 | 73.79/55.34 |
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  | RoBERTa-base-ca-v2 | 89.29 | 98.96 | 79.07 | 74.26 | 83.14 | 87.74/72.58 | 88.72/75.91 | 89.50/76.63 | 73.64/55.42 |
@@ -186,5 +184,5 @@ The models published in this repository are intended for a generalist purpose an
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  When third parties, deploy or provide systems and/or services to other parties using any of these models (or using systems based on these models) or become users of the models, they should note that it is their responsibility to mitigate the risks arising from their use and, in any event, to comply with applicable regulations, including regulations regarding the use of Artificial Intelligence.
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- In no event shall the owner and creator of the models (BSC – Barcelona Supercomputing Center) be liable for any results arising from the use made by third parties of these models.
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  </details>
 
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  ### Training data
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  The training corpus consists of several corpora gathered from web crawling and public corpora.
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+
 
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  | Corpus | Size in GB |
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  |-------------------------|------------|
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  | Catalan Crawling | 13.00 |
 
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  | Nació Digital | 0.42 |
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  | Vilaweb | 0.06 |
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  | Tweets | 0.02 |
 
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  ### Training procedure
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  This is how it compares to the teacher model when fine-tuned on the same downstream tasks:
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+ | Model \ Task| NER (F1) | POS (F1) | STS-ca (Comb) | TeCla (Acc.) | TEca (Acc.) | VilaQuAD (F1/EM)| ViquiQuAD (F1/EM) | CatalanQA (F1/EM) | XQuAD-ca <sup>1</sup> (F1/EM) |
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  | ------------|:-------------:| -----:|:------|:------|:-------|:------|:----|:----|:----|
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  | RoBERTa-large-ca-v2 | 89.82 | 99.02 | 83.41 | 75.46 | 83.61 | 89.34/75.50 | 89.20/75.77 | 90.72/79.06 | 73.79/55.34 |
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  | RoBERTa-base-ca-v2 | 89.29 | 98.96 | 79.07 | 74.26 | 83.14 | 87.74/72.58 | 88.72/75.91 | 89.50/76.63 | 73.64/55.42 |
 
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  When third parties, deploy or provide systems and/or services to other parties using any of these models (or using systems based on these models) or become users of the models, they should note that it is their responsibility to mitigate the risks arising from their use and, in any event, to comply with applicable regulations, including regulations regarding the use of Artificial Intelligence.
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+ In no event shall the owner and creator of the models (BSC) be liable for any results arising from the use made by third parties of these models.
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  </details>