Upload TFRobertaForSequenceClassification

README.md

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+---
+base_model: cardiffnlp/twitter-roberta-base-sentiment-latest
+tags:
+- generated_from_keras_callback
+model-index:
+- name: Roberta-base-financial-sentiment-analysis
+  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. -->
+
+# Roberta-base-financial-sentiment-analysis
+
+This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base-sentiment-latest](https://huggingface.co/cardiffnlp/twitter-roberta-base-sentiment-latest) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Train Loss: 0.0030
+- Train Accuracy: 0.9988
+- Validation Loss: 0.3030
+- Validation Accuracy: 0.9421
+- Epoch: 9
+
+## 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': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 5e-05, 'decay_steps': 3030, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
+- training_precision: float32
+
+### Training results
+
+| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
+|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
+| 0.3811     | 0.8688         | 0.2107          | 0.9324              | 0     |
+| 0.1596     | 0.9561         | 0.2188          | 0.9295              | 1     |
+| 0.1074     | 0.9706         | 0.2296          | 0.9373              | 2     |
+| 0.0846     | 0.9743         | 0.2560          | 0.9315              | 3     |
+| 0.0277     | 0.9921         | 0.3173          | 0.9247              | 4     |
+| 0.0151     | 0.9959         | 0.2698          | 0.9488              | 5     |
+| 0.0071     | 0.9975         | 0.3498          | 0.9353              | 6     |
+| 0.0038     | 0.9992         | 0.3178          | 0.9479              | 7     |
+| 0.0054     | 0.9979         | 0.3035          | 0.9431              | 8     |
+| 0.0030     | 0.9988         | 0.3030          | 0.9421              | 9     |
+
+
+### Framework versions
+
+- Transformers 4.31.0
+- TensorFlow 2.12.0
+- Datasets 2.14.4
+- Tokenizers 0.13.3

config.json

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+{
+  "_name_or_path": "cardiffnlp/twitter-roberta-base-sentiment-latest",
+  "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,
+  "id2label": {
+    "0": "negative",
+    "1": "neutral",
+    "2": "positive"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "negative": 0,
+    "neutral": 1,
+    "positive": 2
+  },
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 514,
+  "model_type": "roberta",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 1,
+  "position_embedding_type": "absolute",
+  "torch_dtype": "float32",
+  "transformers_version": "4.31.0",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 50265
+}

tf_model.h5

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+oid sha256:647428040e09986e0d87a49cc32f6b6d630051b6bc37f4f9d91ec7c9a3a5a248
+size 498881344