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@@ -11,4 +11,27 @@ metrics:
 
 # DistilBERT base model (uncased)
 
-This model is the Multi-Genre Natural Language Inference (MNLI) fine-turned version of the [uncased DistilBERT model](https://huggingface.co/distilbert-base-uncased).
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+This is the [uncased DistilBERT model](https://huggingface.co/distilbert-base-uncased) fine-tuned on [Multi-Genre Natural Language Inference](https://huggingface.co/datasets/multi_nli) (MNLI) dataset for the zero-shot classification task. The model is not case-sensitive, i.e., it does not make a difference between "english" and "English".
+
+## Training
+
+Training is done on a [p3.2xlarge](https://aws.amazon.com/ec2/instance-types/p3/) AWS EC2 instance (1 NVIDIA Tesla V100 GPUs), with the following hyperparameters:
+
+```
+$ run_glue.py \
+    --model_name_or_path distilbert-base-uncased \
+    --task_name mnli \
+    --do_train \
+    --do_eval \
+    --max_seq_length 128 \
+    --per_device_train_batch_size 16 \
+    --learning_rate 2e-5 \
+    --num_train_epochs 5 \
+    --output_dir /tmp/distilbert-base-uncased_mnli/
+```
+
+## Evaluation results
+
+| Task | MNLI | MNLI-mm |
+|:----:|:----:|:----:|
+|      | 82.0 | 82.0 |
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