> ## Documentation Index > Fetch the complete documentation index at: https://portkey-docs-feat-rerank-documentation.mintlify.site/llms.txt > Use this file to discover all available pages before exploring further. # List Fine-tuning Checkpoints ## OpenAPI ````yaml get /fine_tuning/jobs/{fine_tuning_job_id}/checkpoints openapi: 3.0.0 info: title: Portkey API description: >- The Portkey REST API. Please see https://portkey.ai/docs/api-reference for more details. version: 2.0.0 termsOfService: https://portkey.ai/terms contact: name: Portkey Developer Forum url: https://portkey.wiki/community license: name: MIT url: https://github.com/Portkey-AI/portkey-openapi/blob/master/LICENSE servers: - url: https://api.portkey.ai/v1 description: Portkey API Public Endpoint security: - Portkey-Key: [] tags: - name: Assistants description: Build Assistants that can call models and use tools. - name: Audio description: Turn audio into text or text into audio. - name: Chat description: >- Given a list of messages comprising a conversation, the model will return a response. - name: Realtime description: WebSocket proxy for provider Realtime APIs - name: Collections description: Create, List, Retrieve, Update, and Delete collections of prompts. - name: Labels description: Create, List, Retrieve, Update, and Delete labels. - name: Prompt Collections description: Create, List, Retrieve, Update, and Delete prompt collections. - name: PromptPartials description: Create, List, Retrieve, Update, and Delete prompt partials. - name: Prompts description: >- Given a prompt template ID and variables, will run the saved prompt template and return a response. - name: Guardrails description: Create, List, Retrieve, Update, and Delete prompt Guardrails. - name: Completions description: >- Given a prompt, the model will return one or more predicted completions, and can also return the probabilities of alternative tokens at each position. - name: Embeddings description: >- Get a vector representation of a given input that can be easily consumed by machine learning models and algorithms. - name: Rerank description: >- Rerank a list of documents based on their relevance to a query. Supported providers include Cohere, Voyage, Jina, Pinecone, Bedrock, and Azure AI. - name: Fine-tuning description: Manage fine-tuning jobs to tailor a model to your specific training data. - name: Batch description: Create large batches of API requests to run asynchronously. - name: Files description: >- Files are used to upload documents that can be used with features like Assistants and Fine-tuning. - name: Images description: Given a prompt and/or an input image, the model will generate a new image. - name: Models description: List and describe the various models available in the API. - name: Moderations description: >- Given a input text, outputs if the model classifies it as potentially harmful. - name: Configs description: Create, List, Retrieve, and Update your Portkey Configs. - name: Feedback description: Send and Update any feedback. - name: Logs description: Custom Logger to add external logs to Portkey. - name: Integrations description: Create, List, Retrieve, Update, and Delete your Portkey Integrations. - name: Integrations > Workspaces description: Manage workspace access for your Portkey Integrations. - name: Integrations > Models description: Manage model access for your Portkey Integrations. - name: Providers description: Create, List, Retrieve, Update, and Delete your Portkey Providers. - name: Virtual-keys description: Create, List, Retrieve, Update, and Delete your Portkey Virtual keys. - name: Users description: Create and manage users. - name: User-invites description: Create and manage user invites. - name: Workspaces description: Create and manage workspaces. - name: Workspaces > Members description: Create and manage workspace members. - name: MCP Integrations description: Create, List, Retrieve, Update, and Delete MCP Integrations. - name: MCP Integrations > Workspaces description: Manage workspace access for MCP Integrations. - name: MCP Integrations > Capabilities description: List and manage capabilities for MCP Integrations. - name: MCP Integrations > Metadata description: Get MCP Integration metadata and sync info. - name: MCP Servers description: >- Create, List, Retrieve, Update, and Delete MCP Servers (workspace instances of MCP Integrations). - name: MCP Servers > Capabilities description: List and manage capabilities for MCP Servers. - name: MCP Servers > User Access description: List and manage user access for MCP Servers. - name: MCP Servers > Connections description: List and manage user connections for MCP Servers. - name: Api-Keys description: Create, List, Retrieve, Update, and Delete your Portkey API keys. - name: Logs Export description: Exports logs service. - name: Audit Logs description: Get audit logs for your Portkey account. - name: Analytics description: >- Get analytics over different data points like requests, costs, tokens, etc. - name: Analytics > Graphs description: Get data points for graphical representation. - name: Analytics > Summary description: Get overall summary for the selected time bucket. - name: Analytics > Groups description: Get grouped metrics for the selected time bucket. - name: Usage Limits Policies description: Manage usage limits policies to control total usage over time - name: Rate Limits Policies description: Manage rate limits policies to control request or token rates - name: Model Pricing description: Model pricing configurations for 2300+ LLMs across 40+ providers - name: Secret-References description: >- Create, List, Retrieve, Update, and Delete secret references to external secret managers. paths: /fine_tuning/jobs/{fine_tuning_job_id}/checkpoints: servers: - url: https://api.portkey.ai/v1 description: Portkey API Public Endpoint - url: SELF_HOSTED_GATEWAY_URL description: Self-Hosted Gateway URL get: tags: - Fine-tuning summary: | List checkpoints for a fine-tuning job. operationId: listFineTuningJobCheckpoints parameters: - in: path name: fine_tuning_job_id required: true schema: type: string example: ft-AF1WoRqd3aJAHsqc9NY7iL8F description: | The ID of the fine-tuning job to get checkpoints for. - name: after in: query description: >- Identifier for the last checkpoint ID from the previous pagination request. required: false schema: type: string - name: limit in: query description: Number of checkpoints to retrieve. required: false schema: type: integer default: 10 responses: '200': description: OK content: application/json: schema: $ref: '#/components/schemas/ListFineTuningJobCheckpointsResponse' security: - Portkey-Key: [] Virtual-Key: [] - Portkey-Key: [] Provider-Auth: [] Provider-Name: [] - Portkey-Key: [] Config: [] - Portkey-Key: [] Provider-Auth: [] Provider-Name: [] Custom-Host: [] x-code-samples: - lang: curl label: Default source: > curl https://api.portkey.ai/v1/fine_tuning/jobs/ftjob-abc123/checkpoints \ -H "x-portkey-api-key: $PORTKEY_API_KEY" \ -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" - lang: curl label: Self-Hosted source: > curl SELF_HOSTED_GATEWAY_URL/fine_tuning/jobs/ftjob-abc123/checkpoints \ -H "x-portkey-api-key: $PORTKEY_API_KEY" \ -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" - lang: python label: Default source: > from portkey_ai import Portkey client = Portkey( api_key = "PORTKEY_API_KEY", virtual_key = "PROVIDER_VIRTUAL_KEY" ) checkpoints_list = client.fine_tuning.jobs.checkpoints.list(fine_tuning_job_id="") print(checkpoints_list) - lang: javascript label: Default source: | import Portkey from 'portkey-ai'; const client = new Portkey({ apiKey: 'PORTKEY_API_KEY', virtualKey: 'PROVIDER_VIRTUAL_KEY' }); async function main() { const checkpointsList = await client.fineTuning.jobs.checkpoints.list("") console.log(checkpointsList) } main(); - lang: python label: Self-Hosted source: > from portkey_ai import Portkey client = Portkey( api_key = "PORTKEY_API_KEY", virtual_key = "PROVIDER_VIRTUAL_KEY", base_url = "SELF_HOSTED_GATEWAY_URL" ) checkpoints_list = client.fine_tuning.jobs.checkpoints.list(fine_tuning_job_id="") print(checkpoints_list) - lang: javascript label: Self-Hosted source: | import Portkey from 'portkey-ai'; const client = new Portkey({ apiKey: 'PORTKEY_API_KEY', virtualKey: 'PROVIDER_VIRTUAL_KEY', baseUrl: 'SELF_HOSTED_GATEWAY_URL' }); async function main() { const checkpointsList = await client.fineTuning.jobs.checkpoints.list("") console.log(checkpointsList) } main(); components: schemas: ListFineTuningJobCheckpointsResponse: type: object properties: data: type: array items: $ref: '#/components/schemas/FineTuningJobCheckpoint' object: type: string enum: - list first_id: type: string nullable: true last_id: type: string nullable: true has_more: type: boolean required: - object - data - has_more FineTuningJobCheckpoint: type: object title: FineTuningJobCheckpoint description: > The `fine_tuning.job.checkpoint` object represents a model checkpoint for a fine-tuning job that is ready to use. properties: id: type: string description: >- The checkpoint identifier, which can be referenced in the API endpoints. created_at: type: integer description: The Unix timestamp (in seconds) for when the checkpoint was created. fine_tuned_model_checkpoint: type: string description: The name of the fine-tuned checkpoint model that is created. step_number: type: integer description: The step number that the checkpoint was created at. metrics: type: object description: Metrics at the step number during the fine-tuning job. properties: step: type: number train_loss: type: number train_mean_token_accuracy: type: number valid_loss: type: number valid_mean_token_accuracy: type: number full_valid_loss: type: number full_valid_mean_token_accuracy: type: number fine_tuning_job_id: type: string description: >- The name of the fine-tuning job that this checkpoint was created from. object: type: string description: The object type, which is always "fine_tuning.job.checkpoint". enum: - fine_tuning.job.checkpoint required: - created_at - fine_tuning_job_id - fine_tuned_model_checkpoint - id - metrics - object - step_number x-code-samples: name: The fine-tuning job checkpoint object example: | { "object": "fine_tuning.job.checkpoint", "id": "ftckpt_qtZ5Gyk4BLq1SfLFWp3RtO3P", "created_at": 1712211699, "fine_tuned_model_checkpoint": "ft:gpt-3.5-turbo-0125:my-org:custom_suffix:9ABel2dg:ckpt-step-88", "fine_tuning_job_id": "ftjob-fpbNQ3H1GrMehXRf8cO97xTN", "metrics": { "step": 88, "train_loss": 0.478, "train_mean_token_accuracy": 0.924, "valid_loss": 10.112, "valid_mean_token_accuracy": 0.145, "full_valid_loss": 0.567, "full_valid_mean_token_accuracy": 0.944 }, "step_number": 88 } securitySchemes: Portkey-Key: type: apiKey in: header name: x-portkey-api-key Virtual-Key: type: apiKey in: header name: x-portkey-virtual-key Provider-Auth: type: http scheme: bearer Provider-Name: type: apiKey in: header name: x-portkey-provider Config: type: apiKey in: header name: x-portkey-config Custom-Host: type: apiKey in: header name: x-portkey-custom-host ````