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README.md

@@ -1,111 +1,204 @@
 ---
 library_name: peft
 base_model: mistralai/Mistral-7B-v0.1
-license: apache-2.0
-datasets:
-- bitext/Bitext-customer-support-llm-chatbot-training-dataset
-language:
-- en
-tags:
-- text-generation-inference
 ---
 
-# Description
+# Model Card for Model ID
 
-This LoRA adapter was fine-tuned on the `bitext/Bitext-customer-support-llm-chatbot-training-dataset`, specifically by:
-1. Grouping the data on the following `category` column values: `PAYMENT`, `INVOICE`, `REFUND`
-2. Merging `intent` and `response` columns into a new single column called `response_json` that is a JSON object consisting of two keys: `intent` and `response`.
+<!-- Provide a quick summary of what the model is/does. -->
 
-This is what the dataset looks like once it is preprared:
 
-<img src="./payments_dataset.png" alt="drawing" width="1500"/>
 
-It also has the following token distribution (without the prompt template being merged into the input)
+## Model Details
 
-<img src="./token_distribution.png" alt="drawing" width="400"/>
+### Model Description
 
-# How To Use This Model
+<!-- Provide a longer summary of what this model is. -->
 
-## Prompt Template
 
-This adapter was instruction tuned using the following prompt template:
 
-```text
-You are a support agent for a company and you receive requests from customers.
-Your job is to reply to the customer by providing both the intent, which you
-should determine from the customer's request, as well as an appropriate response.
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
 
-Please note that the intent can only be one of the following: check_payment_methods, get_invoice, check_refund_policy, track_refund, payment_issue, check_invoice, get_refund.
+### Model Sources [optional]
 
-Please package your reply in the JSON format.
+<!-- Provide the basic links for the model. -->
 
-Request: {instruction}
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
 
-Reply:
-```
+## Uses
 
-At inference time, just replace/insert `{instruction}` with an actual instruction.
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
 
-## Fine-Tuning
+### Direct Use
 
-This adapter was fine-tuned using Predibase. You can sign up for a free trial and follow along using this notebook to reproduce this adapter: https://colab.research.google.com/drive/1Zzkrr40NRylUnq-pztaypVOoDPS2s9Vr
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
 
-## Example Input and Output
+[More Information Needed]
 
-Input:
+### Downstream Use [optional]
 
-```
-You are a support agent for a company and you receive requests from customers.
-Your job is to reply to the customer by providing both the intent, which you
-should determine from the customer's request, as well as an appropriate response.
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
 
-Please note that the intent can only be one of the following: check_payment_methods, get_invoice, check_refund_policy, track_refund, payment_issue, check_invoice, get_refund.
+[More Information Needed]
 
-Please package your reply in the JSON format.
+### Out-of-Scope Use
 
-Request: can you help me check in which cases can I ask for refunds?
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
 
-Reply:
-```
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure 
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
 
-Output (rendered using pprint, but is a proper JSON with full key-value pairs):
-```python
-{'intent': 'check_refund_policy',
- 'response': "I'll do my best! I completely understand your need to have a "
-             'clear understanding of the situations in which you can request a '
-             'refund. Let me provide you with a comprehensive breakdown:\n'
-             '\n'
-             '1. **Product/Service Defect:** If the product or service you '
-             "purchased has a defect or doesn't meet the description, you are "
-             'typically eligible for a refund.\n'
-             '2. **Cancellation within Grace Period:** Should you change your '
-             'mind and decide to cancel your purchase within the specified '
-             'grace period, you should be able to receive a refund.\n'
-             '3. **Unauthorized Charges:** If you notice any charges on your '
-             "account that you didn't authorize or recognize, we will "
-             'investigate the matter and assist you in obtaining a refund.\n'
-             '4. **Event Cancellation:** If you purchased tickets for an event '
-             'that gets canceled without a rescheduled date, you would usually '
-             'be entitled to a refund.\n'
-             '5. **Duplicate Charges:** If you have been charged multiple '
-             'times for the same item, please inform us, and we will rectify '
-             'the situation promptly.\n'
-             "6. **Non-receipt of Goods:** If you haven't received your "
-             'ordered product within the expected timeframe, you may qualify '
-             'for a refund.\n'
-             '\n'
-             'Please keep in mind that refund policies may vary depending on '
-             "the vendor or service provider. It's always a good idea to "
-             'review their terms and conditions or contact them directly for '
-             'more specific information. If you have any specific concerns or '
-             'need assistance with a particular order, please provide me with '
-             "the necessary details, such as the order number, and I'll be "
-             'glad to assist you further.\n'
-             '\n'
-             'Is there anything else I can help you with today?'}
-```
 
 ### Framework versions
 
-- PEFT 0.8.2
-- Ludwig 0.10.2
+- PEFT 0.10.0

adapter_config.json

@@ -6,22 +6,24 @@
   "fan_in_fan_out": false,
   "inference_mode": true,
   "init_lora_weights": true,
+  "layer_replication": null,
   "layers_pattern": null,
   "layers_to_transform": null,
   "loftq_config": {},
-  "lora_alpha": 16,
-  "lora_dropout": 0.05,
+  "lora_alpha": 32,
+  "lora_dropout": 0,
   "megatron_config": null,
   "megatron_core": "megatron.core",
-  "modules_to_save": null,
+  "modules_to_save": [],
   "peft_type": "LORA",
-  "r": 8,
+  "r": 16,
   "rank_pattern": {},
   "revision": null,
   "target_modules": [
-    "v_proj",
-    "q_proj"
+    "q_proj",
+    "v_proj"
   ],
   "task_type": "CAUSAL_LM",
+  "use_dora": false,
   "use_rslora": false
 }

adapter_model.safetensors

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special_tokens_map.json

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+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
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+    "lstrip": false,
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+}

tokenizer.model

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+size 493443

tokenizer_config.json

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+{
+  "add_bos_token": true,
+  "add_eos_token": false,
+  "added_tokens_decoder": {
+    "0": {
+      "content": "<unk>",
+      "lstrip": false,
+      "normalized": false,
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+      "single_word": false,
+      "special": true
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+  "additional_special_tokens": [],
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+  "eos_token": "</s>",
+  "legacy": true,
+  "model_max_length": 32768,
+  "pad_token": "<unk>",
+  "padding_side": "right",
+  "sp_model_kwargs": {},
+  "spaces_between_special_tokens": false,
+  "tokenizer_class": "LlamaTokenizer",
+  "unk_token": "<unk>",
+  "use_default_system_prompt": false
+}

training_args.bin

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