finetuned_tinybert_spam

README.md

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+---
+base_model: hf-internal-testing/tiny-albert
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: results
+  results: []
+---
+
+<!-- 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 [hf-internal-testing/tiny-albert](https://huggingface.co/hf-internal-testing/tiny-albert) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1315
+- Accuracy: 0.96
+
+## 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: 0.001
+- train_batch_size: 24
+- eval_batch_size: 24
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 25.0
+- num_epochs: 1
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.6937        | 0.1   | 25   | 0.6927          | 0.5115   |
+| 0.6911        | 0.2   | 50   | 0.6770          | 0.613    |
+| 0.4988        | 0.3   | 75   | 0.3574          | 0.886    |
+| 0.2604        | 0.4   | 100  | 0.1720          | 0.9525   |
+| 0.1758        | 0.5   | 125  | 0.1787          | 0.9435   |
+| 0.1964        | 0.6   | 150  | 0.1327          | 0.9615   |
+| 0.1637        | 0.7   | 175  | 0.1269          | 0.9635   |
+| 0.1453        | 0.8   | 200  | 0.1538          | 0.9565   |
+| 0.1563        | 0.9   | 225  | 0.1508          | 0.9575   |
+| 0.1657        | 1.0   | 250  | 0.1315          | 0.96     |
+
+
+### Framework versions
+
+- Transformers 4.40.0
+- Pytorch 2.2.1+cu121
+- Datasets 2.19.0
+- Tokenizers 0.19.1

config.json

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+{
+  "_name_or_path": "hf-internal-testing/tiny-albert",
+  "architectures": [
+    "AlbertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 2,
+  "classifier_dropout_prob": 0.1,
+  "down_scale_factor": 1,
+  "embedding_size": 64,
+  "eos_token_id": 3,
+  "gap_size": 0,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 32,
+  "initializer_range": 0.02,
+  "inner_group_num": 1,
+  "intermediate_size": 128,
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 256,
+  "model_type": "albert",
+  "net_structure_type": 0,
+  "num_attention_heads": 2,
+  "num_hidden_groups": 1,
+  "num_hidden_layers": 2,
+  "num_memory_blocks": 0,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.40.0",
+  "type_vocab_size": 2,
+  "vocab_size": 5000
+}

model.safetensors

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+oid sha256:931af7274dfa317eedecd4a316043d164f8fd7d4534be226e43fe63a8efb5a85
+size 1413520

training_args.bin

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