Upload TFAlbertForSequenceClassification

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_keras_callback
+model-index:
+- name: IntelDAOS20ALBERT_Unbalance
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information Keras had access to. You should
+probably proofread and complete it, then remove this comment. -->
+
+# IntelDAOS20ALBERT_Unbalance
+
+This model is a fine-tuned version of [albert-base-v2](https://huggingface.co/albert-base-v2) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Train Loss: 0.1657
+- Train Accuracy: 0.9610
+- Validation Loss: 0.3170
+- Validation Accuracy: 0.9099
+- Epoch: 6
+
+## 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:
+- optimizer: {'name': 'Adam', 'weight_decay': 0.001, 'clipnorm': 1.0, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': False, 'is_legacy_optimizer': False, 'learning_rate': 3e-05, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
+- training_precision: float32
+
+### Training results
+
+| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
+|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
+| 0.1838     | 0.9610         | 0.3105          | 0.9099              | 0     |
+| 0.1607     | 0.9610         | 0.3048          | 0.9099              | 1     |
+| 0.2077     | 0.9450         | 0.3424          | 0.9099              | 2     |
+| 0.1625     | 0.9580         | 0.3038          | 0.9099              | 3     |
+| 0.1596     | 0.9610         | 0.3226          | 0.9099              | 4     |
+| 0.1548     | 0.9610         | 0.3334          | 0.9099              | 5     |
+| 0.1657     | 0.9610         | 0.3170          | 0.9099              | 6     |
+
+
+### Framework versions
+
+- Transformers 4.29.2
+- TensorFlow 2.12.0
+- Datasets 2.12.0
+- Tokenizers 0.13.3

config.json

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+{
+  "_name_or_path": "albert-base-v2",
+  "architectures": [
+    "AlbertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 2,
+  "classifier_dropout_prob": 0.1,
+  "down_scale_factor": 1,
+  "embedding_size": 128,
+  "eos_token_id": 3,
+  "gap_size": 0,
+  "hidden_act": "gelu_new",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "inner_group_num": 1,
+  "intermediate_size": 3072,
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "albert",
+  "net_structure_type": 0,
+  "num_attention_heads": 12,
+  "num_hidden_groups": 1,
+  "num_hidden_layers": 12,
+  "num_memory_blocks": 0,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "transformers_version": "4.29.2",
+  "type_vocab_size": 2,
+  "vocab_size": 30000
+}

tf_model.h5

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+size 46781688