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3 changed files with 10 additions and 14 deletions

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@ -10,16 +10,16 @@ tags:
license: mit license: mit
pipeline_tag: zero-shot-classification pipeline_tag: zero-shot-classification
datasets: datasets:
- xnli - xlni
metrics: metrics:
- accuracy - accuracy
--- ---
# camembert-base-xnli # camembert-base-xlni
## Model description ## Model description
Camembert-base model fine-tuned on french part of XNLI dataset. <br> Camembert-base model fine-tuned on french part of XLNI dataset. <br>
One of the few Zero-Shot classification model working on french 🇫🇷 One of the few Zero-Shot classification model working on french 🇫🇷
## Intended uses & limitations ## Intended uses & limitations
@ -46,7 +46,7 @@ classifier(sequence, candidate_labels, hypothesis_template=hypothesis_template)
``` ```
- As a premise/hypothesis checker : <br> - As a premise/hypothesis checker : <br>
The idea is here to compute a probability of the form \\( P(premise|hypothesis ) \\) The idea is here to compute a probability of the form \\(P(premise|hypothesis)\\)
```python ```python
# load model and tokenizer # load model and tokenizer
@ -70,7 +70,7 @@ prob_label_is_true[0].tolist() * 100
## Training data ## Training data
Training data is the french fold of the [XNLI](https://research.fb.com/publications/xnli-evaluating-cross-lingual-sentence-representations/) dataset released in 2018 by Facebook. <br> Training data is the french fold of the [XLNI](https://research.fb.com/publications/xnli-evaluating-cross-lingual-sentence-representations/) dataset released in 2018 by Facebook. <br>
Available with great ease using the ```datasets``` library : Available with great ease using the ```datasets``` library :
```python ```python
@ -86,7 +86,6 @@ Main training parameters :
- ```num_train_epochs = 4``` - ```num_train_epochs = 4```
- ```batch_size = 12``` (limited by GPU-memory) - ```batch_size = 12``` (limited by GPU-memory)
- ```weight_decay = 0.01``` - ```weight_decay = 0.01```
- ```metric_for_best_model = "eval_accuracy"```
## Eval results ## Eval results

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@ -11,16 +11,16 @@
"hidden_dropout_prob": 0.1, "hidden_dropout_prob": 0.1,
"hidden_size": 768, "hidden_size": 768,
"id2label": { "id2label": {
"0": "entailment", "0": "contradiction",
"1": "neutral", "1": "neutral",
"2": "contradiction" "2": "entailment"
}, },
"initializer_range": 0.02, "initializer_range": 0.02,
"intermediate_size": 3072, "intermediate_size": 3072,
"label2id": { "label2id": {
"entailment": 0, "contradiction": 0,
"neutral": 1, "neutral": 1,
"contradiction": 2 "entailment": 2
}, },
"layer_norm_eps": 1e-05, "layer_norm_eps": 1e-05,
"max_position_embeddings": 514, "max_position_embeddings": 514,
@ -30,7 +30,7 @@
"output_past": true, "output_past": true,
"pad_token_id": 1, "pad_token_id": 1,
"position_embedding_type": "absolute", "position_embedding_type": "absolute",
"transformers_version": "4.3.3", "transformers_version": "4.4.2",
"type_vocab_size": 1, "type_vocab_size": 1,
"use_cache": true, "use_cache": true,
"vocab_size": 32005 "vocab_size": 32005

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