End of training

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- amazon_reviews_multi
+metrics:
+- accuracy
+- f1
+model-index:
+- name: distilbert-base-multilingual-cased-sentiment-2
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: amazon_reviews_multi
+      type: amazon_reviews_multi
+      args: all_languages
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.7475666666666667
+    - name: F1
+      type: f1
+      value: 0.7475666666666667
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# distilbert-base-multilingual-cased-sentiment-2
+
+This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) on the amazon_reviews_multi dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6067
+- Accuracy: 0.7476
+- F1: 0.7476
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 0.00024
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 33
+- distributed_type: sagemaker_data_parallel
+- num_devices: 8
+- total_train_batch_size: 128
+- total_eval_batch_size: 128
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 500
+- num_epochs: 3
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
+| 0.6885        | 0.53  | 5000  | 0.6532          | 0.7217   | 0.7217 |
+| 0.6411        | 1.07  | 10000 | 0.6348          | 0.7319   | 0.7319 |
+| 0.6057        | 1.6   | 15000 | 0.6186          | 0.7387   | 0.7387 |
+| 0.5844        | 2.13  | 20000 | 0.6236          | 0.7449   | 0.7449 |
+| 0.549         | 2.67  | 25000 | 0.6067          | 0.7476   | 0.7476 |
+
+
+### Framework versions
+
+- Transformers 4.12.3
+- Pytorch 1.9.1
+- Datasets 1.15.1
+- Tokenizers 0.10.3

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