Telco Transformer V1 Chat
Telco Transformer Chat model is a subset to facilitate conversational interactions. The objective is to train a chat model to be good at conversing in a context. The base model is provided with a general comprehension of the telco language. It is then finetuned on curated instruction dataset to improve overall conversation quality.
Telco Transformer V1 Chat is a fine-tuned version of subhashtalluri/Telco_Transformer_1_4. It achieves the following results on the evaluation set:
- Loss: 3.8628
Model Usage
Context Length: 512 tokens
Prompt Definition:
Q): {user question}
A):
Prompt Examples for V1 Chat:
Currently, the model is limited to answering questions about MPLS - Multiprotocol label switching. Please ask questions about MPLS is various forms.
- What is MPLS?
- Describe MPLS?
- When is MPLS used?
- What are the pros and cons of MPLS?
- Why do we need MPLS?
- How does MPLS work?
- What are the drawbacks of MPLS?
- How does routing work in MLPS?
- What is MPLS used for? etc..
Please note: The response is limited to 512 tokens. It will give a compute error when generating beyond this limit.
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 3e-05
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 3.3391 | 0.56 | 50 | 3.9165 |
| 2.5623 | 1.12 | 100 | 3.8315 |
| 3.6035 | 1.69 | 150 | 3.7690 |
| 3.6966 | 2.25 | 200 | 3.7529 |
| 3.3786 | 2.81 | 250 | 3.7020 |
| 1.8281 | 3.37 | 300 | 3.7681 |
| 2.8276 | 3.93 | 350 | 3.7432 |
| 1.4719 | 4.49 | 400 | 3.7911 |
| 1.2252 | 5.06 | 450 | 3.7793 |
| 1.3996 | 5.62 | 500 | 3.7991 |
| 1.1709 | 6.18 | 550 | 3.8068 |
| 0.7002 | 6.74 | 600 | 3.8335 |
| 2.2776 | 7.3 | 650 | 3.8329 |
| 2.0515 | 7.87 | 700 | 3.8596 |
| 2.2111 | 8.43 | 750 | 3.8686 |
| 1.1622 | 8.99 | 800 | 3.8587 |
| 0.7239 | 9.55 | 850 | 3.8628 |
Framework versions
- Transformers 4.39.0.dev0
- Pytorch 2.0.0+cu117
- Datasets 2.10.1
- Tokenizers 0.15.2