End of training

README.md

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+---
+base_model: Prezily/my_awesome_model
+tags:
+- generated_from_trainer
+datasets:
+- amazon_polarity
+metrics:
+- accuracy
+model-index:
+- name: bert_sentiment_2
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: amazon_polarity
+      type: amazon_polarity
+      config: amazon_polarity
+      split: test
+      args: amazon_polarity
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9183333333333333
+---
+
+<!-- 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. -->
+
+# bert_sentiment_2
+
+This model is a fine-tuned version of [Prezily/my_awesome_model](https://huggingface.co/Prezily/my_awesome_model) on the amazon_polarity dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4320
+- Accuracy: 0.9183
+
+## 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: 5e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 3.0
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 1.0   | 375  | 0.3221          | 0.901    |
+| 0.3163        | 2.0   | 750  | 0.3553          | 0.914    |
+| 0.0945        | 3.0   | 1125 | 0.4320          | 0.9183   |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.15.0
+- Tokenizers 0.15.0

config.json

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+{
+  "_name_or_path": "Prezily/my_awesome_model",
+  "activation": "gelu",
+  "architectures": [
+    "DistilBertForSequenceClassification"
+  ],
+  "attention_dropout": 0.1,
+  "dim": 768,
+  "dropout": 0.1,
+  "hidden_dim": 3072,
+  "id2label": {
+    "0": "NEGATIVE",
+    "1": "POSITIVE"
+  },
+  "initializer_range": 0.02,
+  "label2id": {
+    "NEGATIVE": 0,
+    "POSITIVE": 1
+  },
+  "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": "4.35.2",
+  "vocab_size": 30522
+}

model.safetensors

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+size 267832560

runs/Dec15_19-56-08_0280a0825f3a/events.out.tfevents.1702670172.0280a0825f3a.10688.0

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training_args.bin

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