bert-tiny-sst2

README.md

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+---
+base_model: M-FAC/bert-tiny-finetuned-sst2
+tags:
+- generated_from_trainer
+datasets:
+- sst2
+metrics:
+- accuracy
+model-index:
+- name: results
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: sst2
+      type: sst2
+      config: default
+      split: validation
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.8279816513761468
+---
+
+<!-- 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. -->
+
+# results
+
+This model is a fine-tuned version of [M-FAC/bert-tiny-finetuned-sst2](https://huggingface.co/M-FAC/bert-tiny-finetuned-sst2) on the sst2 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4771
+- Accuracy: 0.8280
+
+## 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: 128
+- eval_batch_size: 128
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.2313        | 1.0   | 527  | 0.4771          | 0.8280   |
+| 0.2057        | 2.0   | 1054 | 0.4937          | 0.8257   |
+| 0.1949        | 3.0   | 1581 | 0.5121          | 0.8177   |
+| 0.1904        | 4.0   | 2108 | 0.5100          | 0.8200   |
+| 0.1879        | 5.0   | 2635 | 0.5137          | 0.8211   |
+
+
+### Framework versions
+
+- Transformers 4.34.0.dev0
+- Pytorch 2.0.1+cu117
+- Datasets 2.14.5
+- Tokenizers 0.14.0

config.json

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+{
+  "_name_or_path": "M-FAC/bert-tiny-finetuned-sst2",
+  "architectures": [
+    "BertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "finetuning_task": "sst2",
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 128,
+  "initializer_range": 0.02,
+  "intermediate_size": 512,
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 2,
+  "num_hidden_layers": 2,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "torch_dtype": "float16",
+  "transformers_version": "4.34.0.dev0",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

pytorch_model.bin

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+size 8785836

training_args.bin

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