Duplicate from lewtun/sagemaker-distilbert-emotion

Co-authored-by: Lewis Tunstall <[email protected]>

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.gitignore

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README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- emotion
+metrics:
+- accuracy
+model-index:
+- name: sagemaker-distilbert-emotion
+  results:
+  - task:
+      type: text-classification
+      name: Text Classification
+    dataset:
+      name: emotion
+      type: emotion
+      args: default
+    metrics:
+    - type: accuracy
+      value: 0.921
+      name: Accuracy
+  - task:
+      type: text-classification
+      name: Text Classification
+    dataset:
+      name: emotion
+      type: emotion
+      config: default
+      split: test
+    metrics:
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+      name: loss
+      verified: true
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+duplicated_from: lewtun/sagemaker-distilbert-emotion
+---
+
+<!-- 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. -->
+
+# sagemaker-distilbert-emotion
+
+This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the emotion dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2322
+- Accuracy: 0.921
+
+## 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: 3e-05
+- train_batch_size: 32
+- eval_batch_size: 64
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 500
+- num_epochs: 1
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.9306        | 1.0   | 500  | 0.2322          | 0.921    |
+
+
+### Framework versions
+
+- Transformers 4.12.3
+- Pytorch 1.9.1
+- Datasets 1.15.1
+- Tokenizers 0.10.3

config.json

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+{
+  "_name_or_path": "distilbert-base-uncased",
+  "activation": "gelu",
+  "architectures": [
+    "DistilBertForSequenceClassification"
+  ],
+  "attention_dropout": 0.1,
+  "dim": 768,
+  "dropout": 0.1,
+  "hidden_dim": 3072,
+  "id2label": {
+    "0": "sadness",
+    "1": "joy",
+    "2": "love",
+    "3": "anger",
+    "4": "fear",
+    "5": "surprise"
+  },
+  "initializer_range": 0.02,
+  "label2id": {
+    "anger": "3",
+    "fear": "4",
+    "joy": "1",
+    "love": "2",
+    "sadness": "0",
+    "surprise": "5"
+  },
+  "max_position_embeddings": 512,
+  "model_type": "distilbert",
+  "n_heads": 12,
+  "n_layers": 6,
+  "pad_token_id": 0,
+  "problem_type": "single_label_classification",
+  "qa_dropout": 0.1,
+  "seq_classif_dropout": 0.2,
+  "sinusoidal_pos_embds": false,
+  "tie_weights_": true,
+  "torch_dtype": "float32",
+  "transformers_version": "4.12.3",
+  "vocab_size": 30522
+}

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tokenizer_config.json

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