Upload TFBartForSequenceClassification

README.md

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+---
+library_name: transformers
+license: mit
+base_model: facebook/bart-large-mnli
+tags:
+- generated_from_keras_callback
+model-index:
+- name: zero-shot-prompt-classifier-bart-ft
+  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. -->
+
+# zero-shot-prompt-classifier-bart-ft
+
+This model is a fine-tuned version of [facebook/bart-large-mnli](https://huggingface.co/facebook/bart-large-mnli) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Train Loss: 0.4474
+- Train Accuracy: 0.7843
+- Validation Loss: 1.5942
+- Validation Accuracy: 0.4657
+- Epoch: 4
+
+## 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': False, 'is_legacy_optimizer': False, 'learning_rate': 5e-06, '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 |
+|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
+| 0.9969     | 0.5490         | 0.9182          | 0.6225              | 0     |
+| 0.7647     | 0.6601         | 1.0025          | 0.5441              | 1     |
+| 0.6465     | 0.7157         | 1.1472          | 0.5392              | 2     |
+| 0.5849     | 0.7418         | 1.1974          | 0.5049              | 3     |
+| 0.4474     | 0.7843         | 1.5942          | 0.4657              | 4     |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- TensorFlow 2.18.0-dev20240717
+- Datasets 2.21.0
+- Tokenizers 0.19.1

config.json

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+{
+  "_name_or_path": "facebook/bart-large-mnli",
+  "_num_labels": 3,
+  "activation_dropout": 0.0,
+  "activation_function": "gelu",
+  "add_final_layer_norm": false,
+  "architectures": [
+    "BartForSequenceClassification"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 0,
+  "classif_dropout": 0.0,
+  "classifier_dropout": 0.0,
+  "d_model": 1024,
+  "decoder_attention_heads": 16,
+  "decoder_ffn_dim": 4096,
+  "decoder_layerdrop": 0.0,
+  "decoder_layers": 12,
+  "decoder_start_token_id": 2,
+  "dropout": 0.1,
+  "encoder_attention_heads": 16,
+  "encoder_ffn_dim": 4096,
+  "encoder_layerdrop": 0.0,
+  "encoder_layers": 12,
+  "eos_token_id": 2,
+  "forced_eos_token_id": 2,
+  "gradient_checkpointing": false,
+  "id2label": {
+    "0": "contradiction",
+    "1": "neutral",
+    "2": "entailment"
+  },
+  "init_std": 0.02,
+  "is_encoder_decoder": true,
+  "label2id": {
+    "contradiction": 0,
+    "entailment": 2,
+    "neutral": 1
+  },
+  "max_position_embeddings": 1024,
+  "model_type": "bart",
+  "normalize_before": false,
+  "num_hidden_layers": 12,
+  "output_past": false,
+  "pad_token_id": 1,
+  "scale_embedding": false,
+  "transformers_version": "4.44.2",
+  "use_cache": true,
+  "vocab_size": 50265
+}

tf_model.h5

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+oid sha256:1e6ebc7886f491d50244a67fb7362a5010337968c38130e80e7232284ab3052e
+size 1629942064