End of training

README.md

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+---
+library_name: transformers
+base_model: seyonec/PubChem10M_SMILES_BPE_450k
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: manotham-finetuneClassfication-AlzheimerDrug
+  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. -->
+
+# manotham-finetuneClassfication-AlzheimerDrug
+
+This model is a fine-tuned version of [seyonec/PubChem10M_SMILES_BPE_450k](https://huggingface.co/seyonec/PubChem10M_SMILES_BPE_450k) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2675
+- Accuracy: 0.9383
+- Precision: 0.9398
+- Recall: 0.9383
+- F1: 0.9382
+
+## 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: 2e-05
+- train_batch_size: 64
+- eval_batch_size: 64
+- 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 | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| No log        | 1.0   | 75   | 0.2011          | 0.9408   | 0.9418    | 0.9408 | 0.9408 |
+| No log        | 2.0   | 150  | 0.2087          | 0.9475   | 0.9475    | 0.9475 | 0.9475 |
+| No log        | 3.0   | 225  | 0.2427          | 0.945    | 0.9457    | 0.945  | 0.9450 |
+| No log        | 4.0   | 300  | 0.2497          | 0.9417   | 0.9424    | 0.9417 | 0.9416 |
+| No log        | 5.0   | 375  | 0.2675          | 0.9383   | 0.9398    | 0.9383 | 0.9382 |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.5.0+cu121
+- Datasets 3.1.0
+- Tokenizers 0.19.1

config.json

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+{
+  "_name_or_path": "seyonec/PubChem10M_SMILES_BPE_450k",
+  "architectures": [
+    "RobertaForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 0,
+  "classifier_dropout": null,
+  "eos_token_id": 2,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "roberta",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 6,
+  "pad_token_id": 1,
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.44.2",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 52000
+}

model.safetensors

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runs/Nov01_07-01-24_e8e40170c1b4/events.out.tfevents.1730444612.e8e40170c1b4.9863.2

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training_args.bin

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