summary model

README.md

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+---
+license: apache-2.0
+language:
+- en
+library_name: transformers
+---
+
+# Model Card: bart_fine_tuned_model-v2
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+## Model Name
+
+## bart_fine_tuned_model-v2
+
+### Model Description
+
+<!-- This model represents a fine-tuned version of the facebook/bart-large model, specifically adapted for the task of Resume Summarization. The model has been trained to efficiently generate concise and relevant summaries from extensive resume texts. The fine-tuning process has tailored the original BART model to specialize in summarization tasks based on a specific dataset.. -->
+This model represents a fine-tuned version of the facebook/bart-large model, specifically adapted for the task of Resume Summarization. The model has been trained to efficiently generate concise and relevant summaries from extensive resume texts. The fine-tuning process has tailored the original BART model to specialize in summarization tasks based on a specific dataset.
+
+### Model information
+
+-**Base Model: derekiya/bart_fine_tuned_model-v2**
+
+
+-**Finetuning Dataset: To be made available in the future.**
+
+### Training Parameters
+
+- **Evaluation Strategy: epoch:**
+- **Learning Rate: 5e-5**
+- **Per Device Train Batch Size: 8:** 
+- **Per Device Eval Batch Size: 8**
+- **Weight Decay: 0.01**
+- **Save Total Limit: 5**
+- **Number of Training Epochs: 10**
+- **Predict with Generate: True**
+- **Gradient Accumulation Steps: 1**
+- **Optimizer: paged_adamw_32bit**
+- **Learning Rate Scheduler Type: cosine**
+
+
+## how to use
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+**1.** Install the transformers library:
+
+**pip install transformers**
+
+**2.** Import the necessary modules:
+
+      import torch
+      from transformers import BartTokenizer, BartForConditionalGeneration
+
+**3.** Initialize the model and tokenizer:
+
+      model_name = 'derekiya/bart_fine_tuned_model-v2'
+      tokenizer = BartTokenizer.from_pretrained(model_name)
+      model = BartForConditionalGeneration.from_pretrained(model_name)
+
+**4.** Prepare the text for summarization:
+
+      text = 'Your resume text here'
+      inputs = tokenizer(text, return_tensors="pt", truncation=True, padding="max_length")
+
+**5.** Generate the summary:
+
+    min_length_threshold = 55
+    summary_ids = model.generate(inputs["input_ids"], num_beams=4, min_length=min_length_threshold, max_length=150, early_stopping=True)
+    summary = tokenizer.decode(summary_ids[0], skip_special_tokens=True)
+
+**6.** Output the summary:
+
+    print("Summary:", summary)
+
+## Model Card Authors
+
+Dereje Hinsermu
+
+## Model Card Contact
+

config.json

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+{
+  "_name_or_path": "facebook/bart-large-cnn",
+  "_num_labels": 3,
+  "activation_dropout": 0.0,
+  "activation_function": "gelu",
+  "add_final_layer_norm": false,
+  "architectures": [
+    "BartForConditionalGeneration"
+  ],
+  "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,
+  "early_stopping": true,
+  "encoder_attention_heads": 16,
+  "encoder_ffn_dim": 4096,
+  "encoder_layerdrop": 0.0,
+  "encoder_layers": 12,
+  "eos_token_id": 2,
+  "force_bos_token_to_be_generated": true,
+  "forced_bos_token_id": 0,
+  "forced_eos_token_id": 2,
+  "gradient_checkpointing": false,
+  "id2label": {
+    "0": "LABEL_0",
+    "1": "LABEL_1",
+    "2": "LABEL_2"
+  },
+  "init_std": 0.02,
+  "is_encoder_decoder": true,
+  "label2id": {
+    "LABEL_0": 0,
+    "LABEL_1": 1,
+    "LABEL_2": 2
+  },
+  "length_penalty": 2.0,
+  "max_length": 142,
+  "max_position_embeddings": 1024,
+  "min_length": 56,
+  "model_type": "bart",
+  "no_repeat_ngram_size": 3,
+  "normalize_before": false,
+  "num_beams": 4,
+  "num_hidden_layers": 12,
+  "output_past": true,
+  "pad_token_id": 1,
+  "prefix": " ",
+  "scale_embedding": false,
+  "task_specific_params": {
+    "summarization": {
+      "early_stopping": true,
+      "length_penalty": 2.0,
+      "max_length": 142,
+      "min_length": 56,
+      "no_repeat_ngram_size": 3,
+      "num_beams": 4
+    }
+  },
+  "torch_dtype": "float32",
+  "transformers_version": "4.31.0",
+  "use_cache": true,
+  "vocab_size": 50264
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 0,
+  "decoder_start_token_id": 2,
+  "early_stopping": true,
+  "eos_token_id": 2,
+  "forced_bos_token_id": 0,
+  "forced_eos_token_id": 2,
+  "length_penalty": 2.0,
+  "max_length": 142,
+  "min_length": 56,
+  "no_repeat_ngram_size": 3,
+  "num_beams": 4,
+  "pad_token_id": 1,
+  "transformers_version": "4.31.0"
+}

pytorch_model.bin

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+version https://git-lfs.github.com/spec/v1
+oid sha256:031e4b4460dd4ff71dfe9aac405f384bfe6936c5aaed04a302463dc324943b10
+size 1625537802

special_tokens_map.json

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+{
+  "bos_token": {
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "cls_token": {
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "mask_token": {
+    "content": "<mask>",
+    "lstrip": true,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "<pad>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "sep_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer_config.json

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+{
+  "add_prefix_space": false,
+  "bos_token": {
+    "__type": "AddedToken",
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "clean_up_tokenization_spaces": true,
+  "cls_token": {
+    "__type": "AddedToken",
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "__type": "AddedToken",
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "errors": "replace",
+  "mask_token": {
+    "__type": "AddedToken",
+    "content": "<mask>",
+    "lstrip": true,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "model_max_length": 1024,
+  "pad_token": {
+    "__type": "AddedToken",
+    "content": "<pad>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "sep_token": {
+    "__type": "AddedToken",
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "tokenizer_class": "BartTokenizer",
+  "unk_token": {
+    "__type": "AddedToken",
+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  }
+}